Category Archives: Goals

Image Theory: Principles, Goals, and Plans in Decision Making. Acta Psychologica 1987

  1. Idea that decision making is represented as images, each with different purposes:
    1. goals
    2. what would be the result of obtaining those goals
    3. plans to achieve goals
    4. anticipated results of plans <I suppose they mean near-term, because the end points are just #1>
  2. “Decisions consist of (1) adopting or rejecting potential candidates to be new principles, goals, or plans, and (2) determining whether progress toward goals is being made, i.e., whether the aspired-to future and the anticipated results of the plan implementation correspond.”
  3. Decisions are made either based on:
    1. Compatibility between candidates and existing goals, as well as compatibility with desired future states
    2. Potential reward of goal/plan
  4. <Some things here feel conflated, assume it will be cleared up>
  5. Is based on schemas.  “Images (…) are schemata that are specific to decision behavior and represent the decision maker’s guiding principles relevant to some sphere of decision making.  They also represent the decision maker’s goals in that sphere, what he or she is doing to reach those goals, and his or her view of how well those efforts are succeeding.”
  6. Self-image is how we see ourselves.  Self-image is made of principles, which drive selection of goals
  7. Trajectory image is where we see our plan taking us (both end points, and along the way).  Made up of goals (can be concrete, specific, vague, abstract).
  8. Action image is composed of plans
  9. Goal adoption is accepting the endpoint of a plan
  10. Plans are abstract, made concrete through tactics
    1. Not all tactics must be completely ironed out – items can be left to be dealt with as the plan unfolds
    2. Tactics may have a dependency order, or may be independent (so can be undertaken in any order or concurrently)
  11. The projected image consists of the anticipated events and states that one foresees occurring (1) if one adopts a particular candidate plan in order to attain a specific goal or (2) if one continues with the plans that already have been adopted and that currently are being implemented.”  Deals with expected outcomes
  12. Decisions are of two forms:
    1. Adoption: accept/reject parts of images
    2. Progress: are things going as they should according to plan, if things aren’t going well, a plan may need to be rejected and another on adopted.  If a new plan can’t be found, the goal may have to be rejected
  13. Decisions are made based on compatibility (does it fit well enough – above some threshold – doesn’t have to be perfect) and profitability (what is the reward)
    1. Violations of compatibility may not always be fully conscious, could lead to some emotional sense that something isn’t right
    2. By default we accept things as compatible and only discard with enough evidence.  Favors status quo
  14. Doubt in terms of likelihood of decision success discounts its reward (go by expected reward)
  15. Decisions made based on rejecting those that are incompatible and then selecting from those left the most profitable
  16. Adoption and the evolution of images – how images change over time (developmentally) <skipping>
  17. Future directions
  18. <Not a fruitful read>
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Social Cognitive Theory of Self-Regulation. Bandura. Organizational Behavior and Human Decision Processes 1991.

<Useful link http://homepages.rpi.edu/~verwyc/bandura.htm>

  1. Self-regulation has 3 major sources:
    1. Monitoring behavior, and the results
    2. Judgement of behavior relative personal standards and environment
    3. “affective self-reaction” self-reward or punishment based on outcomes of behavior
  2. Self-regulation is also related to personal agency
  3. <Just based on the language this guy uses this paper is dubious.  Redolent of snowing that philosophers use.>
  4. <Some points here are obvious, but I will try to note them briefly anyway>
  5. In order to do planning we must be able to do symbolic manipulation
  6. Planning is not only a factor of external environment – self reflection allows us to control our behavior, and we have to understand that our actions are meaningful.  This comes from self-monitoring
  7. If cause and effect are close in time, understanding implications through self-monitoring is simpler
  8. RL idea – actions with good outcomes are reinforced and actions with bad outcomes are suppressed
  9. Distinguishes between self-monitoring and self-observation, but its not clear to me what the distinction is.
  10. “Moreover, people differ in their self-monitoring orientations in the extent to which they guide their actions in terms of personal standards or social standards of behavior (Snyder, 1987).  Those who have a firm sense of identity and are strongly oriented toward fulfilling their personal standards display a high level of self-directedness.  Those who have a firm sense of identity and are strongly oriented toward fulfilling their personal standards display a high level of self-directedness.  Those who are not much committed to personal standards adopt a pragmatic orientation, tailoring their behavior to fit whatever the situation seems to call for.  They become adept at reading social cues, remembering those that have predictive value and varying their self-presentation accordingly.”
  11. We develop personal standards partially based on social feedback, also we often judge our performance on objectively scored tasks relative to others
  12. “In everyday life, people imbue remarkably varied activities, many seemingly trivial in character, with high evaluative significance as when they invest their self-esteem in how far they can toss a shot-put ball.”
  13. People are less satisfied with accomplishments when the results are partially the result of the actions of others.  Likewise they may be upset if something happens that is bad and their fault, but if not their fault the feeling of regret is reduced
  14. People motivate themselves by providing self-incentives – exercising and then having some ice cream.  Results have shown that self-incentivising is important for regulating behavior, especially in unstructured environments
  15. <Ok now we are getting to more useful stuff>
  16. Functioning of Self-regulatory Systems
  17. Self-efficacy system. Belief in efficacy has a huge impact in how/what decisions are made: “People’s beliefs in their efficacy influence the choices they make, their aspirations, how much effort they mobilize in a given endeavor, how long they persevere in the face of difficulties and setbacks, whether their thought patterns are self-hindering or self-aiding, the amount of stress they experience in coping with taxing environmental demands, and their vulnerability to depression.”
  18. Self-efficacy also ifluences how we attribute success/failure.  People with high belief of self-efficacy will attribute good outcomes to themselves and bad to external causes and vice versa
  19. We tend to enjoy tasks at which we deem ourselves efficacious, and derive pleasure from mastering them (becoming even more efficacious)
  20. The negative feedback model
    1. Discuss “the basic regulator in control theory” <like a linear quadratic regulator>
    2. “psychobiologic homeostatic theories”
    3. “cybernetic TOTE model”
    4. Equilibration (sole source of motivation in Piaget’s theory)
  21. The general idea in negative feedback models are that simply try to reduce the disparity between the current state and the goal state
  22. “A regulatory process in which matching a standard begets inertness does not characterize human self-motivation.  Such a feedback control system would produce circular action that leads nowhere.  Nor could people be stirred to action until they receive feedback of a short-coming.”
  23. Some form of feedback is necessary for regulation of motivation, but people self-motivate by taking goals before any feedback occurs.  Furthermore, goal-setting allows one to set a basis by which regulation can later take place. So this negative feedback doesn’t explain high-level planning well, but perhaps its ok for low-level: “… anticipative or proactive control operates as the primary system in the mobilization of motivation and reactive feedback specifies the further adjustments in effort <why only effort> needed to accomplish desired goals.”
  24. “Human self-motivation relies on both discrepancy production and discrepancy reduction.” (must have both feedback and goals)
  25. feedbackgoals
  26. Hierarchical Structure of Goal Systems
  27. “… proximal goals are not simply subordinate servitors of valued loftier ones as commonly depicted in machinelike hierarchical control systems.  Through engagement of the self-system, subgoals invest activities with personal significance.”  Indeed, sometimes, the motivation to performance of subgoals can override progress toward the actual goal.
  28. Aspirational standards: the standard you set for yourself determines the level you accept when satisficing
  29. <Ok, stopping here, think its enough>

Methods of Heuristics. Groner, Groner, Bischof (eds). Book 1983

<Pretty neat book actually, contains proceedings of multidisciplinary symposium on Methods of Heuristics.  Has a chapter by Minsky, for example.  No time to read the whole book.  George Polya, of Polya’s urn fame devoted a great deal of his work to heuristics, and is discussed here as well.  He was invited but health prevented him.  Piaget was also slated to talk, but died the day he was originally asked to speak – his longtime collaborator did come, though. De Groot is also here but I think I have it covered from previous reading.>

Chapter 6: Heuristics and Cognition in Complex Systems.  Dorner

  1. Well defined problems have the following features:
    1. Goal state is known
    2. Rules of the domain are known
  2. Often, following constraints are added
    1. State changes only through the planner
    2. Problem is not too big
    3. Is fully observable
  3. In complex systems
    1. The goal is vauge, perhaps multi-factor – goals that have multiple weighed aspects (this makes the problem into more of a reward problem than graph search)
    2. Results of all operators are unknown, or perhaps, not even all the operators are known
    3. Partial observability
  4. Move on to how to start attacking problem (such as where to start making unknown items known)
  5. When anchoring the problem by nailing down unknown items, a stopping rule may be needed, especially in cases with real-valued information.  The idea is to stop once a reasonable resolution level has been reached.  This should be the minimal amount needed to reach the goal
  6. In real life, people often attempt to achieve goals that are mutually exclusive, but are not aware of it
  7. In some cases, setting subgoals or simpler heuristic goals in place of the true goal can lead to poor behavior: “When a S [a participant] in the tailor shop game reasoned about a way to get more profit by selling his products, the S finally decided to strive for a higher sales rate.  First he tried to get a higher rate of sales by advertisement.  When this had not sufficient effect, the S decided to lower the prices.  This measure was effective; the S sold his whole production, without making any profit, as he sold products for less than his costs.”
  8. In some cases also, the interim goal gets all importance, and the individual forgets about the original goal entirely (this happens alot in science, where answering a preceding question becomes of significant interest, and can be a large distraction)
  9. People might also not choose goals at all.  Lindblom (1964) discussed a few symptoms of this sort of behavior:
    1. Thematic vagabonding: they continually change their course of action and therefore never make significant progress
    2. Encapsulation: over-commitment to some approach
    3. Both are escape tendencies where working on the actual problem is avoided: “They do not solve the problems the should solve (but can’t), but rather those they can (but shouldn’t).  Often the replacement of a final goal by an interim goal may be a kind of encapsulation.”
  10. Another potential problem is that individuals only collect or pay attention to data that fits in with their preconcieved (and potentially incorrect) conception of the problem.  This is called the use of a dogmatically entrenched system.  “That means that the individual never again gets negative feedback; his system of assumptions becomes dogmatic.”
  11. These “cognitive degenerations” can be due to a feeling of incompetence.  Seeking out information requires both that one doesn’t have enough information, but also that one is capable of obtaining information and using it.  Dogmatism is the wrong way of securing a feeling of competence.
  12. <…>

Toward a General Theory of Expertise. Ericsson, Smith (Eds). Book 1991.

<Notes will be very sparse>

Chapter 1: Prospects and Limits of the Empirical Study of Expertise: An Introduction.  Ericcson, Smith

  1. For chess, De Groot set up well-defined tasks for analyzing chess expertise not by watching players go through full games (which would be too diffuse in terms of the entire state space), and instead presented chess positions and asked players to only select the next move
    1. This isn’t exactly possible though, because in general you can’t exactly solve a board position in chess due to complexity
  2. De Groot used “thinking aloud” experiments by players of different skill levels
  3. De Groot found that when using the thinking aloud approach with next move queries, experts and masters took around 10 minutes: “In the beginning, the players familiarized themselves with the chess position, evaluated the position for strengths and weaknesses, and identified a range of promising moves.  Later they explored in greater depth the consequences of a few of those moves.  On average, both masters and experts considered more than thirty move possibilities involving Black and White and considered three or four distinctly different first moves.”
  4. He found that masters and experts didn’t differ in their rollout depth
  5. The differences between the two groups; but masters generally mention the best move during familiarization, whereas experts found the best move later on.  This implies that move selection in chess generally comes down not to improved computation but rather improved board-value representation. “De Groot (1978, p. 316) argued that mastery in ‘the field of shoemaking, painting, building, [or] confectionary’ is due to a similar accumulation of experiential linkings.”
  6. During tests on board memorization (exposure from 2-10 seconds) improved recall was linked to improved playing ability.  Chase and Simon followed up on these experiments
    1. For random board configurations (not arrived at during natural play), recall between masters and novices was equivalent… “showing that the superior memory performance of the master depends on the presence of meaningful relations between the chess pieces, the kinds of relations seen in actual chess games.”
    2. Recall of piece location did not occur smoothly over time – there would be bursts which corresponded with logical chunking; masters were found to have different <larger> chunk sizes
    3. “Chase and Simon (1093) found that the number of chunks recalled by chess players at all skill levels was well within the limit of around 7 +/- 2 <so it seems not to be the case that masters are simply better at all recall tasks>.  They attributed the difference in memory performance between strong and weak players to the fact that the more expert chess players were able to recognize more complex chunks, that is, chunks with a larger number of chess pieces per chunk.”
  7. Estimated 3,000 hours to be an expert, 30,000 to be a master
  8. Better expert memory in areas of expertise has been shown in many other domains.  Although experts may acutally forget parts of the information, it is usually in the case where that information is irrelevant (for example, forgetting symptoms that aren’t related to the diagnosis of a patient)
  9. (p.20) “The types of differences found in a wide range of domains of expertise are remarkably consistent with those originally noted by de Groot (1978) in the domain of chess.  Expert performers tend to retrieve a solution method (e.g., next moves for a chess position) as part of the immediate comprehension of the task, whereas less experienced subjects have to construct a representation of the task deliberately and generate a step-by-step solution, as shown by research on physics problems (…) and algebra-word problems (…).  Medical experts generate their diagnoses by studying the symptoms (forward reasoning), whereas less experienced medical students tend to check correctness of a diagnoses by inspecting relevant symptoms (backward reasoning) (Patel & Groen, chapter 4, this volume).”
  10. <Next paragraph> On the same theme, expert performers have a body of knowledge that not only is more extensive than for nonexperts but is also more accessible (…).  Whenever knowledge is relevant, experts appear to access it efficiently (…).  The experts are therefore able to notice inconsistencies rapidly, and thus inconsistent hypotheses are rejected rapidly in favor of the correct diagnosis (…).  On presentation, information in the problem is integrated with the relevant domain knowledge (Patel & Groen, chapter 4, this volume).”
  11. p.22 discusses domain specific memorization schemes
    1. In categorization of physics problems, experts categorized them based on solution methodology that could be applied, whereas novices categorized them based on superficial aspects of the problem, such as the types of objects being discussed.
    2. Studies of board recall in chess show that masters also utilize forms of long term memory (not just short-term) in the task.  Additionally, chunks are formed such that in many cases there is overlap so that there are also encodings of how chunks relate to each other.
    3. Recall also depends on task; as mentioned doctors may forget symptoms irrelevant to diagnosis, and similar results with studies on programming
  12. Studying performance of experts in the lab can be difficult because tasks in the lab must match the same tasks that the experts are experienced in
  13. Experts have faster response time, better ability to plan ahead, and better memory (all in the particular domain of expertise)
  14. Chase and Simon theory: (p.26)
    1. Difference in ability is related to immediate access to relevant knowledge (retrieving chess board positions/relevant chunking) (1973 – perception in chess)
    2. Theoretical account of how experts extract best moves from long-term memory
    3. Chunks serve as cues to activate best move recall
    4. “The chess masters’ richer vocabulary of chunks thus played a critical role in the storage and retrieval of superior chess moves.”
  15. Accounts focusing on practice and learning: (p.27)
    1. Improvement in a task often follows a power law <serious diminishing returns> (Newell & Rosenbloom, 1981).   They also consider chunking here
    2. Fitts proposed 3 stages in skill aquisition:
      1. Cognitive: cognitive effort to understand the task and what parts to pay attention to
      2. Associative: “… making the cognitive process efficient to allow rapid retrieval and perception of required information.”
      3. Autonomous: “… performance is automatic, conscious cognition is minimal.”
    3. “First, it is important to distinguish between practice and mere exposure or experience.  It is well known that learning requires feedback in order to be effective.  Hence, in environments with poor or even delayed feedback, learning may be slow or nonexistent.”
    4. In some domains, performance never really improves, even after enormous amounts of practice – this is often the case when the domain is chaotic.  Time spent doing something isn’t always a good measure of proficiency
  16. Accounts focusing on memory functioning: (p.28)
    1. “The Chase-Simon hypothesis that superior memory of the expert reflects the storage of more complex independent chunks in short-term memory has been seriously questioned, and most of the empirical evidence also suggests storage of interrelated information in long-term memory, as mentioned earlier.”
    2. Experts happen to develop excellent memory for the task of interest, although setting out with the goal just to develop the same memory ability (with no improvement in the actual task itself) one can develop memory on the level of a master quite quickly
    3. There is a school of thought that holds that in the above situation, those that trained specifically for recall are using only short-term memory, whereas experts go through the loop of accessing long term memory, but do that very quickly so it seems the same as short-term memory.
    4. Accounts focusing on the ability to plan and reason: (p.31)
      1. Chess masters can play “mental chess,” keeping track of the progress of a game simply by being told the move sequence.  “This research raises the possibility that acquisition of expert-level chess skill involves the development of skilled memory for chess positions.”
    1. “Charness (1981) found that the depth to which a possible move sequence for a chess position was explored was closely related to the level of chess skill, at least for chess players at or below the level of chess experts.” <but I think I remember reading that there wasn’t much difference between experts and masters, oh immediately they say that is what de Groot found.>
    2. “One should also keep in mind that the task of searching for a move for a middle-game chess position is not designed to measure the capacity to make deep searches and hence may well reflect pragmatic criteria for sufficient depth of exploration to evaluate a prospective move.”
    3. “In the absence of a strict time constraint, there appears to be no clear limit to the depth to which a chess master can explore a position.” <due to the ability to play mental chess perfectly>
    4. Abilities of chess masters to play mental chess “… was consistent with the characteristics of skilled-memory theory (Chase & Ericsson, 1982; Ericsson & Staszewski, 1989).”
    5. In medical diagnoses, doctors must integrate evidence, not all of which may be available at the same time
  17. “The most effective approach to organizing the results across different domains of expertise is to propose a small number of learning mechanisms that can account for the development of similar performance characteristics in different domains within the limits of human informational capabilities.  There is now overwhelming empirical support for the theory of acquisition of skill with mechanisms akin to those originally proposed by Chase and Simon (1973).”  Which they themselves claimed was just a preliminary attempt at a theory.

Chapter 2: Experts in Chess: The Balance Between Knowledge and Search.  Charness

  1. “Because of its unique properties – particularly its rating scale [elo] and its method of recording games – chess offers cognitive psychologists an ideal task environment in which to study skilled performance.  It has been called a Drosophila, or fruit fly, for cognitive psychology (Charness, 1989; Simon & Chase, 1973).”
  2. Here, what is considered is “… the opportunity for trading off knowledge and search to reach a a single goal: skilled play.”
  3. Also considers how computer chess works
  4. Research on chess found that between experts and masters, search size was about the same, but recall/chunking efficiency (not # of chunks) was better in masters.  The conclusion therefore was “… that chess skill depended on a large knowledge base indexed through thousands of familiar chess patterns.  They theorized that recognition drives move generation in search, enabling the skilled player to examine promising paths, but leaving the less skilled to wander down less productive paths.” <Better heuristic accuracy>
  5. “Nonetheless, further research has revealed some apparent flaws in a strictly recognition-based theory.  Other studies have brought into question the notion that recall of briefly seen chess positions would depend on the type of short-term memory system simulated by Simon and Gilmartin (1973).”  Masters were still better at move selection for unnatural board configurations (even though their recall and that of experts was the same).  This, along with a few other results showed “… a simple recognition-association theory was inadequate to account for all the data.”
  6. “Both I (Charness, 1976) and Frey and Adesman (1976) demonstrated that when chess players recalled briefly seen positions, information was not retrieved from short term memory.  My study showed virtually no interference when players had to perform interpolated processing between exposure to the chess position and recall… Clearly a more sophisticated view of skilled memory, such as that proposed by Chase and Ericsson (1982), Ericsson (1985), and Ericsson and Staszewski (1989), is needed to account for recall effects.  These theorists have stressed the importance of domain-specific, easily activated, long-term-memory retrieval structures in recall performance.”
  7. In a longitudinal study, Charness retested a player after a 9 year delay, where the player started at average tournament level strength and ended up an international master.  “DH [the player] showed virtually no change in search (depth, extent), but did show major changes in recall, evaluation, and chunking… The major changes seemed to be pattern-related… the significant factor in skilled chess play at the top levels is what is searched, not how exhaustively or deeply the search is conducted.”
  8. Masters are less impacted by time pressure than lower-quality players
  9. There is also literature on abacus calculation (Hatano, Miyake, & Binks, 1977) <I know that those skilled with the abacus can also do “mental calculation” and can keep track of bead positions and changes fully in their head, just as chess masters can>
  10. A questionnaire (partially dealing with openings) is a better predictor of chess ability than the recall task
  11. <Lots of discussion of size of chess, number of openings, middle, and endgame knowledge, other aspects of metagame, learning from books as opposed to direct play>
  12. “Incidental” serial memory: good players can often recall large portions of a game right after the match, and masters can sometimes recall entire games from months or years earlier.
    1. Game trajectories can be encoded partially in terms of openings, closings, and other logical chunks
  13. “It is probably fair to characterize much of human learning as pattern learning.  An unanswered question is that of whether certain patterns are easier to learn (and model) than others.  Both psychometric investigations and neuro-psychological research provide evidence that all processing is not the same: Some people are better at spatial tasks; others at verbal tasks.”

Chapter 4: The General and Specific Nature of Medical Expertise: A Critical Look. Patel, Groen

  1. “Two fundamental empirical findings in research on expert-novice comparisons have been the phenomena of enhanced recall and forward reasoning.  The first refers to the fact that experts have superior memory skills in recognizing patterns in their domain of expertise.  This is extensively reviewed by Ericsson and Smith (chapter 1, this volume).  The second pertains to the finding that in solving routine problems in their domains, expert problem-solvers tend to work ‘forward’ from the given information to the unknown.  With the exception of Anzai’s study (chapter 3, this volume <on reasoning of physics problems, I didn’t have time to read>), this is not so extensively treated in this volume, but it has been discussed at length in a recent article by Hunt (1989)…”
  2. For details on the Hunt paper, check this out, <turns out forward and backward have different meanings than what I am used to, and the type of planning I am considering at the moment is actually the backward style, as defined here>
  3. “It might be noted that the distinction is frequently made, perhaps more generally, in terms of goal-based (backward) versus knowledge-based (forward) heuristic search (e.g. Hunt, 1989).”
  4. “The distinction between forward and backward reasoning is closely related to another distinction between strong problem-solving methods, which are highly constrained by the problem-solving environment, and weak methods, which are only minimally constrained.  As Hunt pointed out, the distinctions are logically independent.  Forward reasoning, however, is highly error-prone in the absence of adequate domain knowledge because there are no built-in checks in the legitimacy of the inferences.  Therefore, success in using forward reasoning is constrained by the environment because a great deal of relevant knowledge is necessary.  Hence, it is a strong method for all practical purposes.  In contrast, backward reasoning is slower and may make heavy demands on working memory (because one has to keep track of things as goals and hypotheses).  It is, therefore, most likely to be used when domain knowledge is inadequate, in which case there is a need for a method of reasoning that is minimally hampered by this lack of knowledge.  Hence, backward reasoning usually is a symptom of a weak method.”
  5. Here the focus isn’t on differences between experts and novices, but rather “… an emphasis on the factors determining accurate performance and the robustness of the recall and forward-reasoning phenomena under variations of these factors… these phenomena are not as closely related as was implied by what Ericsson and Smith (chapter 1, this volume) refer to as the original theory.  Specifically, there appears to be a ceiling effect associated with the recall of clinical cases.  Beyond that level, however, there continues to be a strong relation between diagnostic accuracy and the use of forward reasoning.”
  6. Development from novice to expert is a 3 stage process:
    1. “… development of adequate knowledge-structure representations.”
    2. learning what is relevant and irrelevant in a problem
    3. “… learning how to use these relevant representations in an efficient fashion”
  7. Study presented data in a very structured (non-naturalistic manner)
  8. In identifying forward reasoning, did some graph-representation <although exactly how isn’t totally clear>
  9. “Forward reasoning corresponds to an oriented path from a fact to a hypothesis.  Thus, forward-directed rules are identified whenever a physician attempts to generate a hypothesis from the findings in a case.  Backward-directed rules correspond to an oriented path from a hypothesis to a fact.”
  10. They then asked other experts for causal rules explaining each case, and transformed them into production rules.
  11. Experts and “subexperts” (the next level below, but above “intermediate” – in this case it meant asking doctors questions about a medical issue outside their specialization) had the same recall, although diagnostic accuracy decreased
  12. An earlier study which seems to form the basis of this chapter(Patel & Groen 1986) found that all cases where pure forward reasoning were used corresponded to correct diagnoses, and that in any case where forward reasoning was not used
  13. Those working outside of their domain of expertise used a combination of forward and backward reasoning
  14. <skipping a bit>
  15. In the problems studied here, recall (as was studied by De Groot, among others) was not an accurate metric of performance due to ceiling effects (experts and subexperts both had perfect recall, although their actual performance in diagnosis differed).  There is actually a nonmonotonic relationship between recall and accuracy in theses studies (there were 5 levels of expertise)
  16. Previous studies assumed recall, diagnostic accuracy, and forward reasoning were all correlated.  “Thus, a theory that simply assumes that the development of expertise is related to the development of better representations cannot be true.”
  17. The findings argue against a couple of theories:
    1. Argues that medical diagnosis is not simply pattern recognition
    2. Argues against the idea that rules cannot be structured into some kind of hierarchy
    3. “Both of these theories posit a close relationship between chunk size in working memory and performance in problem-solving tasks.  Hence, they predict a monotonically increasing relationship between recall and diagnostic accuracy, which as we have seen, does not hold.”
  18. Results argue in favor of SOAR model (Laird, Rosenbloom, Newell 1985) (seems to be a pretty GOFAI model).  Has its own chunking system, and allows for forward and backward reasoning
  19. Argue for 3 kinds of expertise:
    1. Generic: development of adequate representations (for example experts and subexperts had the same recall)
    2. Specific: <not really clear on the point they are making here>
    3. Domain-independent: weak methods – used when there is not sufficient base information, and information must be searched for.  “In contrast, strong methods are more akin to decision making than to search and are highly dependent on an adequate knowledge base.”
  20. In the studies on physics problems, there is good evidence that problem solving is a mixture of forward and backward reasoning.  Forward reasoning is used on routine parts of problems, and backward reasoning on “nonroutine situations”
  21. That is backward reasoning can be used to “stitch together” a logical argument in situations that are difficult somehow (either because of lack of expertise, or because the problem is just hard)
  22. Argue that this form of generic expertise (at least being able to identify relevant parts of a problem, discard the rest, and use backward reasoning where there is a lack of expertise in that exact domain).  This is how doctors making diagnoses outside of their field of expertise function
  23. “Intermediates conduct irrelevant searches, whereas experts do not.  Novices do not conduct irrelevant searches simply because they do not have a knowledge base to search.”

Chapter 10: Techniques for Representing Expert knowledge

<Lots of the stuff here falls under categories of classical AI, linear algebra dimension reduction, hierarchical clustering, just making a concrete note about one item of interest>

 

  1. “Indeed, some of the continuing research themes have to do with how the organization of concepts for an expert differs from that for a novice…”
  2. The nature of the question requires questions about particular small testable aspects of the task of interest (such as recalling chess positions, as opposed to playing through games of chess)
  3. Major issue is how to elicit and then describe expertise
  4. Both direct (interviews, thinking out loud, observation of task performance, closed curves <see below>) and indirect methods (such as giving pairwise similarities and running through MDS, or hierarchical clustering)
  5. IMG_20140905_141807640~2[1]
  6. “Reitman (1976) asked a master of the game of Go to draw closed curves around related stones involved in a position in the game.  Figure 10.4 illustrates several aspects of his responses.  Two positions are displayed, with the master’s encircling of related stones.  In addition, each stone bears a number that represents the ordinal position in which that stone was placed on the board in a recall task six months later <!>.  Note that the recall order matches the closed curves to a remarkable degree: Nearly always, all stones of an encircled chunk were recalled before moving on to another chunk.  This regularity of behavior supports claims for the validity of the information contained in the originally closed curves.”
Tagged ,

Motives and Goals. Fishbach, Toure-Tillery. Book chapter, NOBA 2013.

  1. A goal is a cognitive representation of a desired state <a couple of references>
  2. Motivation, on the other hand, is “… the psychological driving force that enables action in the pursuit of that goal (Lewin 1935).”
  3. Goals can be very concrete ex/walk on mars, or more abstract or vaguely defined and may never be concretely completed ex/eat healthy food
  4. Motivation can be extrinsic or intrinsic, depend on personality, cues can prime goals
    1. Activation of motivation can be conscious or nonconscious
  5. Goal commitment derives from the expected utility of undertaking the goal (goodness of success, likelyhood of success)
  6. “In memory, goals are organized in associative networks, which connect each goal to corresponding means (i.e., activities or objects that contribute to goal attainment …).”
    1. Being fit may be associated with spending time with someone who you exercise with
  7. “Soon after goal priming, the motivation to act on a goal peaks, and then slowly declines after some delay, as the person moves away from the prime or after she pursues the goal (…)”
  8. Activation of goal and motivation levels have impact on many aspects of behavior, and even perception
  9. Self regulation split into two phases:
    1. Deliberative: deciding what goals to undertake.  Encourages consideration of high-level options, but also inhibits action
    2. Implemental: “planning specific actions related to the selected goal.”  In this stage there is a focus on achieving a goal “…through immediate action…” but can lead to people being overly-optimistic about costs in achieving goal
  10. Two orientations during pursuit of goal are:
    1. Prevention: focus on safety, “views goals as ‘oughts'” (risk averse)
    2. Promotion: views goals as “ideals,” more aspirational
  11. Cybernetic process of self-regulation:
    1. “Self-regulation depends on feelings that arise from comparing actual progress to expected progress. During goal pursuit, an individual calculates the discrepancy between her current state (i.e., all goal-related action completed so far) and her desired end state, and then directs action toward closing that gap (Miller, Galanter, & Pribram, 1960; Powers, 1973).” <Read these>
    2. Is a sort of self-regulating process.  Making faster than expected progress leads to positive feelings and “coasting,” whereas slower than expected progress leads to negative feelings and harder work to achieve goal <I suppose the point being you end up finishing pretty close when you expected to regardless of what happened in the interim because of this form of regulation>
  12. Completing actions influences self-regulation:
    1. Commitment: based on the expected utility of achieving goal
    2. Progress: basically s’-s
  13. When previous actions are interpreted as a sign of commitment to goal, they tend to focus more energy on that goal.  On the other hand, when it is interpreted as progress, generally less effort is placed on achieving the goal it is related to (and may focus on other goals)
  14. Self-control is necessary when achieving two goals conflict (often in terms of goals where one is near-term and one is long-term but more important)
    1. These conflicts must be conscious before self-control is used to deal with them
  15. Discussion of ego-depletion (self-control as limited resource) <but I don’t believe in this as it is often described>

The Course of Motivation. Toure-Tillery, Fishbach. Journal of Consumer Psychology 2011.

  1. Explores motivation and goals, considers two aspects:
    1. Attaining a “focal” goal (“outcome-focused dimension”)
    2. Doing things “right” while achieving that goal (“means-focused dimension”)
  2. Identifies conditions where motivation to achieve focal goal decreases during goal pursuit <normally it increases I believe>
  3. Propose that motivation to “do things right” has a U-shape
  4. “We define a goal as a cognitive representation of a desired state…”
  5. “Motivation refers to the psychological force that enables action (Lewin, 1935). We suggest that motivation can manifest
    itself by increased effort and persistence aimed at reaching a goal’s desired state…”  called outcome-focused motivation

    1. Means-focused motivation, on the other hand, is a desire to do things properly in pursuit of the goal
  6. “classic goal-gradient effect”
  7. Once a goal is achieved, motivation drops below baseline (just before achievement, it is as high as it gets) – normally
  8. A few possible explanations of goal-gradient effect:
    1. It is unpleasant to leave things unfinished
    2. Near the goal, each action feels like it is accomplishing much more than actions taken earlier
    3. Prospect theory, and reference points (it is most painful when failing a task at the very end), so in order to avoid increasingly strong negative feelings if there is something that causes task failure, people are willing to invest more and more energy
  9. On the other hand, goal-gradient effect isn’t always observed:
    1. Ongoing tasks that have no clear ending (staying fit/in shape)
    2. Lack of external goal priming (by some cue)
    3. Just finishing a task (can be worn out from significant exertion of just finishing another task, and motivation drops below baseline)
    4. Type of task matters as well (selecting for purchasing vs selecting that expresses taste is high and low depleting, respectively; level of effort impacts later behavior)
    5. Pursuit of multiple goals
    6. If things are easier than expected, individual may “coast” to the end, likewise if things are going poorly, the individual may want to invest extra energy
    7. In continuous tasks, positive milestones also lead to reduced motivation
  10. In terms of behavior according to multiple goals, doing well in one often caused a slip (indulgence) in some other area
  11. Research on self regulation holds that people consider if a goal is worth pursuing (commitment), and potentially if the pace of undertaking the goal is adequate (progress)
  12. People are more aggressive during commitment than progress <but this seems at odds with the goal-gradient effect>
  13. When people have a low initial level of commitment, they construe actions as being related to commitment, but when commitment starts high, actions are construed to be in the progress phase
  14. When people consider a task at a more abstract, meta level, they are more likely to construe action as commitment, and undertake similar tasks (is putting on sunscreen just that, or is it preventing cancer – if the latter, more likely to put on a hat)
  15. When choices are presented as part of a goal, actions are construed more as commitment as well
  16. Means focused motivation
  17. <Reading this quickly so hope I’m not missing big pieces or misreading anything>
  18. People may use “proper means” for a few reasons
    1. To become more skillfull
    2. May fit certain goals better (may be related to whether people are risk-sensitive or averse)
    3. Doing things “correctly” can be good for self-image
    4. On the other hand, relaxing standards can be important because it may involve investing energy in things that are ultimately not important
      1. Standards may be relaxed just enough to prevent negative self image
  19. “The course of means-focused motivation: slacking in the middle”
  20. Classically, studies on sequences show that beginning and end are most salient and easy to remember (primacy/recency)
    1. People felt better at a task if they were told they were doing well at the beginning or end, as opposed to the middle
  21. Also study showed that Jews are more likely to light Hanukah candles at the beginning and end of holiday (ha!)
  22. “Simultaneous activation of outcome- and means-focused motivations”
  23. More investment in goal-directed behavior at beginning (commitment) or end (goal gradient) interacts with slacking-in-the-middle while performing tasks
    1. At the end, may be a conflict to finish quickly, but also to do it “correctly”
  24. Because of these interactions, studies have to be designed carefully