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6.4f. The Frame Problem (The Frame Problem on PhilPapers)

See also:
Anselme, Patrick & French, Robert M. (1999). Interactively converging on context-sensitive representations: A solution to the frame problem. Revue Internationale de Philosophie 53 (209):365-385.   (Google)
Abstract: While we agree that the frame problem, as initially stated by McCarthy and Hayes (1969), is a problem that arises because of the use of representations, we do not accept the anti-representationalist position that the way around the problem is to eliminate representations. We believe that internal representations of the external world are a necessary, perhaps even a defining feature, of higher cognition. We explore the notion of dynamically created context-dependent representations that emerge from a continual interaction between working memory, external input, and long-term memory. We claim that only this kind of representation, necessary for higher cognitive abilities such as counterfactualization, will allow the combinatorial explosion inherent in the frame problem to be avoided
Clark, Andy (2002). Global abductive inference and authoritative sources, or, how search engines can save cognitive science. Cognitive Science Quarterly 2 (2):115-140.   (Cited by 2 | Google | More links)
Abstract: Kleinberg (1999) describes a novel procedure for efficient search in a dense hyper-linked environment, such as the world wide web. The procedure exploits information implicit in the links between pages so as to identify patterns of connectivity indicative of “authorative sources”. At a more general level, the trick is to use this second-order link-structure information to rapidly and cheaply identify the knowledge- structures most likely to be relevant given a specific input. I shall argue that Kleinberg’s procedure is suggestive of a new, viable, and neuroscientifically plausible solution to at least (one incarnation of) the so-called “Frame Problem” in cognitive science viz the problem of explaining global abductive inference. More accurately, I shall argue that
Crockett, L. (1994). The Turing Test and the Frame Problem: AI's Mistaken Understanding of Intelligence. Ablex.   (Cited by 19 | Google)
Abstract: I have discussed the frame problem and the Turing test at length, but I have not attempted to spell out what I think the implications of the frame problem ...
Dennett, Daniel C. (1984). Cognitive wheels: The frame problem of AI. In C. Hookway (ed.), Minds, Machines and Evolution. Cambridge University Press.   (Cited by 139 | Annotation | Google)
Dreyfus, Hubert L. & Dreyfus, Stuart E. (1987). How to stop worrying about the frame problem even though it's computationally insoluble. In Zenon W. Pylyshyn (ed.), The Robot's Dilemma. Ablex.   (Annotation | Google)
Fetzer, James H. (1990). The frame problem: Artificial intelligence meets David Hume. International Journal of Expert Systems 3:219-232.   (Cited by 13 | Google | More links)
Fodor, Jerry A. (1987). Modules, frames, fridgeons, sleeping dogs, and the music of the spheres. In Zenon W. Pylyshyn (ed.), The Robot's Dilemma. Ablex.   (Cited by 56 | Google)
Fodor, Jerry A. (1989). Modules, frames, fridgeons, sleeping dogs. In Modularity in Knowledge Representation and Natural-Language Understanding. Cambridge: MIT Press.   (Google)
Fodor, Jerry A. (1987). Modules, frames, fridgeons. In Modularity In Knowledge Representation And Natural-Language Understanding. Cambridge: Mit Press.   (Google)
Haselager, W. F. G. & Van Rappard, J. F. H. (1998). Connectionism, systematicity, and the frame problem. Minds and Machines 8 (2):161-179.   (Cited by 11 | Google | More links)
Abstract:   This paper investigates connectionism's potential to solve the frame problem. The frame problem arises in the context of modelling the human ability to see the relevant consequences of events in a situation. It has been claimed to be unsolvable for classical cognitive science, but easily manageable for connectionism. We will focus on a representational approach to the frame problem which advocates the use of intrinsic representations. We argue that although connectionism's distributed representations may look promising from this perspective, doubts can be raised about the potential of distributed representations to allow large amounts of complexly structured information to be adequately encoded and processed. It is questionable whether connectionist models that are claimed to effectively represent structured information can be scaled up to a realistic extent. We conclude that the frame problem provides a difficulty to connectionism that is no less serious than the obstacle it constitutes for classical cognitive science
Haugeland, John (1987). An overview of the frame problem. In Zenon W. Pylyshyn (ed.), The Robot's Dilemma. Ablex.   (Cited by 17 | Annotation | Google)
Hayes, Patrick (1987). What the frame problem is and isn't. In Zenon W. Pylyshyn (ed.), The Robot's Dilemma. Ablex.   (Cited by 25 | Annotation | Google)
Hendricks, Scott (2006). The frame problem and theories of belief. Philosophical Studies 129 (2):317-33.   (Google | More links)
Abstract: The frame problem is the problem of how we selectively apply relevant knowledge to particular situations in order to generate practical solutions. Some philosophers have thought that the frame problem can be used to rule out, or argue in favor of, a particular theory of belief states. But this is a mistake. Sentential theories of belief are no better or worse off with respect to the frame problem than are alternative theories of belief, most notably, the “map” theory of belief
Horgan, Terry & Timmons, Mark (2009). What does the frame problem tell us about moral normativity? Ethical Theory and Moral Practice 12 (1).   (Google)
Abstract: Within cognitive science, mental processing is often construed as computation over mental representations—i.e., as the manipulation and transformation of mental representations in accordance with rules of the kind expressible in the form of a computer program. This foundational approach has encountered a long-standing, persistently recalcitrant, problem often called the frame problem; it is sometimes called the relevance problem. In this paper we describe the frame problem and certain of its apparent morals concerning human cognition, and we argue that these morals have significant import regarding both the nature of moral normativity and the human capacity for mastering moral normativity. The morals of the frame problem bode well, we argue, for the claim that moral normativity is not fully systematizable by exceptionless general principles, and for the correlative claim that such systematizability is not required in order for humans to master moral normativity
Janlert, Lars-Erik (1987). Modeling change: The frame problem. In Zenon W. Pylyshyn (ed.), The Robot's Dilemma. Ablex.   (Cited by 23 | Google)
Korb, Kevin B. (1998). The frame problem: An AI fairy tale. Minds and Machines 8 (3):317-351.   (Cited by 1 | Google | More links)
Abstract:   I analyze the frame problem and its relation to other epistemological problems for artificial intelligence, such as the problem of induction, the qualification problem and the "general" AI problem. I dispute the claim that extensions to logic (default logic and circumscriptive logic) will ever offer a viable way out of the problem. In the discussion it will become clear that the original frame problem is really a fairy tale: as originally presented, and as tools for its solution are circumscribed by Pat Hayes, the problem is entertaining, but incapable of resolution. The solution to the frame problem becomes available, and even apparent, when we remove artificial restrictions on its treatment and understand the interrelation between the frame problem and the many other problems for artificial epistemology. I present the solution to the frame problem: an adequate theory and method for the machine induction of causal structure. Whereas this solution is clearly satisfactory in principle, and in practice real progress has been made in recent years in its application, its ultimate implementation is in prospect only for future generations of AI researchers
Lormand, Eric (1990). Framing the frame problem. Synthese 82 (3):353-74.   (Cited by 9 | Annotation | Google | More links)
Abstract:   The frame problem is widely reputed among philosophers to be one of the deepest and most difficult problems of cognitive science. This paper discusses three recent attempts to display this problem: Dennett's problem of ignoring obviously irrelevant knowledge, Haugeland's problem of efficiently keeping track of salient side effects, and Fodor's problem of avoiding the use of kooky concepts. In a negative vein, it is argued that these problems bear nothing but a superficial similarity to the frame problem of AI, so that they do not provide reasons to disparage standard attempts to solve it. More positively, it is argued that these problems are easily solved by slight variations on familiar AI themes. Finally, some discussion is devoted to more difficult problems confronting AI
Lormand, Eric (1998). The frame problem. In Robert A. Wilson & Frank F. Keil (eds.), MIT Encyclopedia of the Cognitive Sciences (MITECS). MIT Press.   (Google)
Abstract: From its humble origins labeling a technical annoyance for a particular AI formalism, the term "frame problem" has grown to cover issues confronting broader research programs in AI. In philosophy, the term has come to encompass allegedly fundamental, but merely superficially related, objections to computational models of mind in AI and beyond
Lormand, Eric (1994). The holorobophobe's dilemma. In Kenneth M. Ford & Z. Pylylshyn (eds.), The Robot's Dilemma Revisited. Ablex.   (Cited by 2 | Google | More links)
Abstract: Much research in AI (and cognitive science, more broadly) proceeds on the assumption that there is a difference between being well-informed and being smart. Being well-informed has to do, roughly, with the content of one’s representations--with their truth and the range of subjects they cover. Being smart, on the other hand, has to do with one’s ability to process these representations and with packaging them in a form that allows them to be processed efficiently. The main theoretical concern of artificial intelligence research is to solve "process-and-form" problems: problems with finding processes and representational formats that enable us to understand how a computer could be smart
Maloney, J. Christopher (1988). In praise of narrow minds. In James H. Fetzer (ed.), Aspects of AI. D.   (Google)
McCarthy, John & Hayes, Patrick (1969). Some philosophical problems from the standpoint of artificial intelligence. In B. Meltzer & Donald Michie (eds.), Machine Intelligence 4. Edinburgh University Press.   (Cited by 1919 | Google | More links)
McDermott, Drew (1987). We've been framed: Or, why AI is innocent of the frame problem. In Zenon W. Pylyshyn (ed.), The Robot's Dilemma. Ablex.   (Cited by 15 | Annotation | Google)
Murphy, Dominic (2001). Folk psychology meets the frame problem. Studies in History and Philosophy of Modern Physics 32 (3):565-573.   (Google)
Murphy, D. (2001). Folk psychology meets the frame problem - W. F. G. Haselager, cognitive science and folk psychology (london: Sage publications, 1997), X + 165 pp. ISBN 0-761-95425-2 hardback £55.00; ISBN 0-761-95426-0 paperback £17.99. Studies in History and Philosophy of Science Part C 32 (3):565-573.   (Google)
Pollock, John L. (1997). Reasoning about change and persistence: A solution to the frame problem. Noûs 31 (2):143-169.   (Cited by 4 | Google | More links)
Pylyshyn, Zenon (1996). The frame problem blues. Once more, with feeling. In K. M. Ford & Z. W. Pylyshyn (eds.), The Robot's Dilemma Revisited: The Frame Problem in Artificial Intelligence. Ablex.   (Cited by 2 | Google | More links)
Abstract: For many of the authors in this volume, this is the second attempt to explore what McCarthy and Hayes (1969) first called the “Frame Problem”. Since the first compendium (Pylyshyn, 1987), nicely summarized here by Ronald Loui, there have been several conferences and books on the topic. Their goals range from providing a clarification of the problem by breaking it down into subproblems (and sometimes declaring the hard subproblems to not be the_ real_ Frame Problem), to providing formal “solutions” to certain aspects of the problem. But more often the message has been that the problem is not solvable except in a piecemeal way in special circumstances by some sort of heuristic approximations. It has sometimes also been said that solving the Frame Problem is not only an unachievable goal, but it is also an unnecessary one since_ humans_ do not solve it either; we simply get along as best we can and deal with the problem of planning in ways that, to use Dennett’s phrase, is “good enough for government work”
Pylyshyn, Zenon W. (ed.) (1987). The Robot's Dilemma. Ablex.   (Cited by 148 | Annotation | Google | More links)
Shanahan, Murray & Baars, Bernard J. (2005). Applying global workspace theory to the frame problem. Cognition 98 (2):157-176.   (Cited by 28 | Google | More links)
Shanahan, Murray (online). The frame problem. Stanford Encyclopedia of Philosophy.   (Google)
Sperber, Dan & Wilson, Deirdre (1996). Fodor's frame problem and relevance theory (reply to chiappe & kukla). [Journal (Paginated)].   (Google | More links)
Abstract: Chiappe and Kukla argue that relevance theory fails to solve the frame problem as defined by Fodor. They are right. They are wrong, however, to take Fodor’s frame problem too seriously. Fodor’s concerns, on the other hand, even though they are wrongly framed, are worth addressing. We argue that Relevance thoery helps address them
Sprevak, Mark, The frame problem and the treatment of prediction.   (Google)
Abstract: The frame problem is a problem in artificial intelligence that a number of philosophers have claimed has philosophical relevance. The structure of this paper is as follows: (1) An account of the frame problem is given; (2) The frame problem is distinguished from related problems; (3) The main strategies for dealing with the frame problem are outlined; (4) A difference between commonsense reasoning and prediction using a scientific theory is argued for; (5) Some implications for the..
Waskan, Jonathan A. (2000). A virtual solution to the frame problem. Proceedings of the First IEEE-RAS International Conference on Humanoid Robots.   (Cited by 1 | Google)
Abstract: We humans often respond effectively when faced with novel circumstances. This is because we are able to predict how particular alterations to the world will play out. Philosophers, psychologists, and computational modelers have long favored an account of this process that takes its inspiration from the truth-preserving powers of formal deduction techniques. There is, however, an alternative hypothesis that is better able to account for the human capacity to predict the consequences worldly alterations. This alternative takes its inspiration from the powers of truth preservation exhibited by scale models and leads to a determinate computational solution to the frame problem
Wheeler, Michael (2008). Cognition in context: Phenomenology, situated robotics and the frame problem. International Journal of Philosophical Studies 16 (3):323 – 349.   (Google | More links)
Abstract: The frame problem is the difficulty of explaining how non-magical systems think and act in ways that are adaptively sensitive to context-dependent relevance. Influenced centrally by Heideggerian phenomenology, Hubert Dreyfus has argued that the frame problem is, in part, a consequence of the assumption (made by mainstream cognitive science and artificial intelligence) that intelligent behaviour is representation-guided behaviour. Dreyfus' Heideggerian analysis suggests that the frame problem dissolves if we reject representationalism about intelligence and recognize that human agents realize the property of thrownness (the property of being always already embedded in a context). I argue that this positive proposal is incomplete until we understand exactly how the properties in question may be instantiated in machines like us. So, working within a broadly Heideggerian conceptual framework, I pursue the character of a representation-shunning thrown machine. As part of this analysis, I suggest that the frame problem is, in truth, a two-headed beast. The intra-context frame problem challenges us to say how a purely mechanistic system may achieve appropriate, flexible and fluid action within a context. The inter-context frame problem challenges us to say how a purely mechanistic system may achieve appropriate, flexible and fluid action in worlds in which adaptation to new contexts is open-ended and in which the number of potential contexts is indeterminate. Drawing on the field of situated robotics, I suggest that the intra-context frame problem may be neutralized by systems of special-purpose adaptive couplings, while the inter-context frame problem may be neutralized by systems that exhibit the phenomenon of continuous reciprocal causation. I also defend the view that while continuous reciprocal causation is in conflict with representational explanation, special-purpose adaptive coupling, as well as its associated agential phenomenology, may feature representations. My proposal has been criticized recently by Dreyfus, who accuses me of propagating a cognitivist misreading of Heidegger, one that, because it maintains a role for representation, leads me seriously astray in my handling of the frame problem. I close by responding to Dreyfus' concerns
Wilkerson, William S. (2001). Simulation, theory, and the frame problem: The interpretive moment. Philosophical Psychology 14 (2):141-153.   (Cited by 5 | Google | More links)
Abstract: The theory-theory claims that the explanation and prediction of behavior works via the application of a theory, while the simulation theory claims that explanation works by putting ourselves in others' places and noting what we would do. On either account, in order to develop a prediction or explanation of another person's behavior, one first needs to have a characterization of that person's current or recent actions. Simulation requires that I have some grasp of the other person's behavior to project myself upon; whereas theorizing requires a subject matter to theorize about. The frame problem shows that multiple, true characterizations are possible for any behavior or situation. However, only one or a few of these characterizations are relevant to explaining or predicting behavior. Since different characterizations of a behavior lead to different predictions or explanations, much of the work of interpersonal interpretation is done in the process of finding this characterization - that is, prior to either theorizing or simulating. Moreover, finding this characterization involves extensive knowledge of the physical, cultural, and social worlds of the persons involved