: Schank, R. C., "Dynamic Memory", Cambridge Univ. Press (1983)  Home/Search   Document Not in Database   Summary   Related Articles   Check

....Carbonell and Veloso, 1988] in PRODIGY. However, some discussion at the end of the chapter addresses the first steps towards synergistic multitechnique integration. Derivational anal ogy is a generalized form of case based reasoning [Hammond, 1986, Kolodner, 1984, Riesbeck and Schank, 1989, Schank, 1982, Simpson, 1985, Sycara, 1987] that incorporates case generation from problem solving experience, case organization into an indexed long term case library case retrieval for problem solving case replay during problem solving and feedback to memory on the utility of the retrieved cases. These ....

....the less search required by the problem solver. However searching memory also takes time. Is there, hence, an optimal amount of effort to spend searching memory We assume that the memory is organized in such a way that the match degree increases monotonically with retrieval time [Kolodner, 1984, Schank, 1982] though not necessarily in a linear manner. This means that there is always one (or more) case available to return when retrieval is halted. However if the retrieval time increases, the match value between the case returned and the new problem also increases. We now forrealize this model. Let ....

Schank, R. C. (1982). Dynamic Memory. Cambridge University Press.

....patterns together. These limitations of scripts as self contained chunks are well known, and more compositional approaches have often been advocated in the literature. Schank s MOPs (Memory Organization Packets) were originally conceived as more general chunks which could be combined together [Schank, 1982], and Dyer s BORIS system allowed abstractions to be (manually) overlayed on a base script, as depicted in Figure 1 [Dyer, 1981] The recurring notion of cliches is based around the theme of composing intermediate level descriptions to represent some specific, possibly time varying, phenomenon ....

Schank, R. (1982). Dynamic Memory. Cambridge Univ. Press. 18

.... Our approach to model and execute a special kind of collaboration processes is theoretically based on schema theory [Schank77] According to schema theory, generalized knowledge about a sequential list of the characteristic events involved in a common routine is called a script [Schank77] Schank82] Scripts can be used to organize knowledge, to assist recall, to guide behavior, to predict likely happenings, and to help us to make sense of our current experiences. People know how to behave and what to expect in particular situations by using scripts. Scripts are mental structures ....

Schank, R. C. (1982). Dynamic memory. Hillsdale, NJ: Erlbaum.

.... composition of two more general scripts (purchasing and dining) The idea of building scripts compositionally is, of course, not new: Schank, dissatisfied with the rigidity of his original script idea, later strongly advocated that scripts should be build compositionally out of fragments ( MOPs ) [Schank, 1982]; similarly, Dyer sketched out some general ideas on how this composition might look [Dyer, 1981] We have also been pushing on this idea in our work on composition [Clark and Porter, 1997, Clark and Porter, 1995] as have others [Chapman, 1986, Noy and Hafner, 1998, Levy, 1993] This Working Note ....

Schank, R. (1982). Dynamic Memory. Cambridge Univ. Press. 20

....generates: I regret not having asked for her number in NUART DAYDREAM2. A success reversal control goal is sometimes pursued upon a recalled success. Why do people imagine failures as well as successes in their daydreams It is well known that people learn from actual failures; see, for example: (Schank, 1982; Dyer, 1983a; Dolan and Dyer, 1985) It is reasonable to expect that it is possible to learn from imagined failures as well. By noting the causes of daydreamed failures in memory, one may avoid similar failures in the future. 2.4 Preparation The preparation control goal is activated when ....

....may occur during daydreaming. Neisser s (1982) analysis of the testimony of John Dean shows that he often remembered conversations in terms of his own fantasy about how those conversations should have been, rather than how they actually were. The dynamic episodic memory (Tulving, 1972; Schank, 1982) of DAYDREAMER is its long term memory of personal or vicarious experiences and daydreams. This memory is called dynamic because it is constantly being modified during daydreaming. Thus not only are actual experiences available for use at any point, but so are previously daydreamed ones. This ....

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Schank, R. C. (1982). Dynamic memory. Cambridge: Cambridge University Press.

....out where the actress went to college, and get an alumni directory from that college, I might be able to find out her telephone number. I ll have to find an article about her somewhere. Revision: Daydreaming occurs in the context of a self modifying episodic memory (called a dynamic memory by Schank, 1982). Each time a problem is examined, new information may be available that will enable a better, different, or more creative solution. For example, in DAYDREAM2 the daydreamer does not figure out how to find out the movie star s telephone number, while in DAYDREAM5 after receiving new information he ....

Schank, R. C. (1982). Dynamic memory. Cambridge: Cambridge University Press.

....are not indexed just according to the specific principle the story illustrates, but to an appropriate abstraction of that principle. Expectation Violation Remindings The greatest opportunity for learning takes place when an expectation that you have is violated by experience. This is what Schank (1982) calls failure driven learning. In this case, failure refers to the failure of an expectation to explain an observation, not the failure of an individual to achieve a goal. The failure of an expectation to explain an observation triggers learning. A case based teaching system attempts to ....

Schank, R.C. 1982. Dynamic Memory . Cambridge: Cambridge University Press.

....speed. CREW runs on Macintosh and Windows computers. The Case Retrieval Mechanism A key aspect of case based reasoning (CBR) is its case retrieval mechanism. The first step in computing predictions for a proposed new case is to retrieve one or more similar cases from the case base. According to Schank (1982), CBR adopts the dynamic memory approach of human recall. As demonstrated in exemplary CBR systems (Riesbeck Schank, 1989) this involves a hierarchical storage and retrieval arrangement. Thus, to retrieve the case most similar to a new case, one might, for instance, follow a tree of links that ....

Schank, R (1982) Dynamic Memory. Cambridge Univ. Press. Cambridge.

....gaps in preferences, the fuzzy set theory is now being extended to preference theory (Perny and Roy (1992) Fodor and Roubens (1994) 3.5 . Case based reasoning With respect to decision, one of the most interesting reasoning models emerged recently in AI. This is the case based reasoning model (Schank, 1982, Kolodner et al. 1985, Kolodner and Simpson, 1989) Here, it is acknowledged that when people reason, they do so on cases as a whole, and not on facts isolated as in expert systems. A case is very similar to an object in programming : it describes, with many attributes, a significant chunk of ....

Schank R.-C., 1982, Dynamic memory, Cambridge, University Press.

.... and jointly sufficient 25 See [Murray and Porter, 1988] for an overview of a knowledge intensive learning apprentice system developed within the CYC environment 26 Earlier work of importance to this field includes work by Schank and Kolodner on memory structures for learning and reasoning [Schank, 1982, Kolodner, 1983] and the work on transformational and derivational analogy by Carbonell [Carbonel, 1986] 27 Notable examples are classical induction methods like Version Space [Mitchell, 1982] AQ [Michalski et al. 1983] and ID3 [Quinlan, 1986] KADS II TII.4.3 TR VUB 002 3.0 42 Machine ....

Schank, R. (Ed.). (1982). Dynamic memory. Cambridge University Press, Cambridge.

....interactive solution processes (Kraay, Harker 1996) An additional, more tangible motivation is provided by the fact that there are applications where it is easier or faster to modify past solutions than to develop new ones from the scratch. More detailed introductions to this matter are given by Schank (1982), Kolodner et al. 1985) and Kolodner (1993) 7 3.2. Applicability and Motivation Although CBR was originally used to tackle ill structured problems exposing little structure to be exploited, some recent authors have begun to apply CBR to OR problems. Kraay, Harker (1996) develop a CBR approach ....

SCHANK, R.-C. (1982), Dynamic memory, Cambridge, University Press.

....heavily on Fisher s (1987) Cobweb, which serves as the underlying component of Labyrinth. However, the historical roots of our approach go back ultimately to Feigenbaum s (1963) Epam, which incrementally constructed a discrimination network from unsupervised instances. This work also influenced Schank s (1982) theory of dynamic memory, which claims that the long term store is an interleaved hierarchy, that retrieval involves sorting experience through memory, and that this process leads to memory reorganization. However, our concern with psychological phenomena has led us to incorporate Gluck and ....

Schank, R. C. (1982). Dynamic memory. Cambridge, UK: Cambridge University Press.

....that they hear and those prototypes with which they are familiar. This task is made more diOEcult by the nature of heart sounds, which are low frequency and often low volume. These two aspects of students learning are well captured by the model of human cognition known as case based reasoning (Schank 1982; Hammond 1989) In this model, new experiences are understood by referring to previous experiences stored in memory. To retrieve a relevant experience from memory, the reasoner must possess a similarity metric by which dioeerent cases can be compared. Research reported in Bregman (Bregman 1994) ....

Schank, R. C. (1982). Dynamic Memory. Cambridge, Cambridge University Press.

....experience in performing its various tasks. We view each agent as being able to perform a number of tasks so that it can flexibly respond to the environment. For reasons that we gave in the last section, the problem solving component in the new model is a Case Based Reasoning (CBR) system [25, 26, 17, 24, 20]. CBR, we believe, provides both flexibility and the ability to re use previous experience in solving problems. In addition, CBR is a way of constructing and understanding systems that learn [25, 26] The central component of a Case Based Reasoning system is a dynamic memory: this memory is ....

....the problem solving component in the new model is a Case Based Reasoning (CBR) system [25, 26, 17, 24, 20] CBR, we believe, provides both flexibility and the ability to re use previous experience in solving problems. In addition, CBR is a way of constructing and understanding systems that learn [25, 26]. The central component of a Case Based Reasoning system is a dynamic memory: this memory is indexed in a variety of ways, allowing retrieval of episodes based on different factors or attributes. When an episode has been retrieved, it can be adjusted to form a new solution (the new solution, when ....

Schank, R. C., Dynamic Memory, CUP, 1982.

....in order to determine the reasons for the failure of an action 4 . In both cases, the context in which the action was performed is important, as are the original reasons for performing the action. The more important of these two cases would appear to be that in which an action fails. Schank [24] argues for the importance of failure in learning: we learn more from failure than success. One reason for this is that when an action fails, it shows that either our view of the situation is flawed in some way (some predicted event or state of affairs may be at fault) or that we do not understand ....

Schank, R. C., Dynamic Memory, CUP, 1982.

....were taken up separately. The theory of Dynamic Memory A second aspect of CBR s cognitive model on which we would like to dwell, is the dynamic behaviour of human memory. Being based on the theory of Dynamic Memory, the model claims that memory is dynamically changing with each new experience (Schank, 1982). Thinking of memory as a constantly growing trace of experience seems more plausible than considering it as a static knowledge base, as more traditional cognitive models do. Both Rule Based and Model Based Reasoning reduce the human mind to a mere repository of general principles. When it uses ....

Schank, R. (1982). Dynamic Memory, A Theory of Reminding and Learning in Computers and People, Cambridge: Cambridge University Press.

....Global Hill Climbing approach fails, a more robust but potentially time consuming Case Based Reasoning (CBR) approach may succeed in particular, because it performs conceptual information filtering that may retrieve articles the keyword scheme cannot. The principle behind case based reasoning (Schank, 1982) is that inductive learning is accomplished through the memorization of individual experiences, or cases. These cases are simply experiences of the learner that have been remembered. When new situations are exposed to the learner, the learner is reminded of previous cases which are similar to the ....

Schank, R.C. (1982). Dynamic memory. Cambridge, NY: Cambridge University Press.

....data visualization and analysis environment. 2. A Model of Learning from Inquiry Research in cognitive science provides compelling evidence for the importance of the way knowledge is indexed and organized in a learner s memory in determining his or her ability to draw on it when it is relevant ([Schank 1982], Kolodner 1993] Greeno, Collins Resnick 1997] To be useful in the future, new knowledge must be connected appropriately to existing memory structures and organized in a way that supports its use. To develop these connections and organization requires a three step process. The first step is ....

.... This recognition occurs in situations when one is confronted with a limitation or gap in one s knowledge, such as those that Berlyne describes as curious [Berlyne 1966] Hiebert et al. describe as problematic [Hiebert, et al. 1996] and Schank describes as leading to expectation failures [Schank 1982]. There are two important effects of this recognition. The first is the creation of a desire to learn in order to address the limitation. The second is the creation of a context in memory for integrating new knowledge. The knowledge structures that are activated at the point that a learner ....

Schank, R. C. (1982). Dynamic Memory . Cambridge: Cambridge University Press.

....our claims using the MetVUW Workbench, a system for intelligent retrieval and display of historical meteorological data. 1 Introduction Case retrieval is an important component of case based reasoning. Design of a case retriever requires addressing the indexing problem (Domeshek, 1991; Schank, 1982; Schank and Fano, 1992) the problem of accessing appropriate cases using partial descriptions of their content. In this paper, we argue that solutions to the indexing problem should be developed by an iterative process of design and evaluation, and that this process is to a significant extent an ....

Schank, R. C. (1982). Dynamic Memory. Cambridge University Press, Cambridge, England.

....Knowledge base World Common sense Codes Individual Editor Story planner Scene analyzer Scene planner Scene constructor Material organizer Figure 4. Architecture of AUTEUR Both the story planner and scene planner interact with the knowledge base, which is organised on principles developed by [Schank, 1982] and [Lehnert et al. 1983] such as MOPs, Meta Mops and Conceptual Dependencies. We augment this model with semantic fields that are mainly based on a network of oppositions (e.g. fat vs. slim) Oppositions are needed for the creation of the ambiguous elements within the story. Furthermore, ....

Schank, R. C. (1982). Dynamic memory. New York: Cambridge University Press.

....that analogical access may be based on qualitatively distinct processes from analogical inferencing 2 . Comparison to Current Approaches. Some models of similarity assume smart processes operating over richly articulated representations. Most case based reasoning models have this character (Schank, 1982; Kolodner, 1988) These models are rich enough to capture processes like case alignment and adaptation. But their models of memory access involve intelligent indexing of structured representations, which can predict superhuman access behavior; that is, that people should typically access the best ....

Schank, R. 1982. Dynamic Memory. Cambridge University Press, Cambridge, England.

....introduces a system that incrementally learns new explanations (explanation patterns) SWALE [Kass86, Leake86] is a system that has a memory formed of eXplanation Patterns (XPs) as components. Each XP represents an annotated causal view of an episode or a generalized class of episodes (like MOP [Schank82]) The explanation construction algorithm is activated only at performance. When SWALE is called upon to explain an event, the system can retrieve an entire XP and apply it as a whole. If the new situation is not exactly like the prototypical one represented in the XP, then a new XP can be formed ....

....chunking information together, they exact a toll in inflexibility. What is to be done with situations or things that are not neatly matched by any existing schema Schemata are useful to some extent if combined with other knowledge structures (e.g. rules) Holland has referred to Schank s schema [Schank82] (which Dejong uses) and to how the restaurant script is very inflexible. Even [Schank82] acknowledged the inflexibility of schemas. This leaves the EBL system unable to achieve its goal of concept refinement, thus restricting it to an EBG system. The second point in clarifying DeJong s ....

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Schank, R. C., (1982). Dynamic Memory. Cambridge: Cambridge University Press.

....as gray rectangles in Figure 1) operating on the WM rely heavily on previous experience, we need also a LONG TERM MEMORY (LTM) to account for the role of experience in invention. Our model builds on the blackboard model of WM (Hayes Roth HayesRoth, 1979) and on the dynamic memory model of LTM (Schank, 1982). Basically, changes in the WM generate events used to activate or generate new goals in the AGENDA. A Strategic Control process selects the next CURRENT GOAL from the AGENDA, based on a CONTROL PLAN. Let s elaborate the LTM of our architecture. In an eventdriven architecture, the monitored ....

Schank, R. (1982). Dynamic memory. Cambridge University Press.

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: Schank, R. C., "Dynamic Memory", Cambridge Univ. Press (1983)

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Schank, R. 1982. Dynamic memory. New York: Cambridge University Press.

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