MindPapers: 6.4b. The Frame Problem

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 | Edit)

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 | Edit)

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

Dennett, Daniel C. (1984). Cognitive wheels: The frame problem of AI. In Minds, Machines and Evolution. Cambridge University Press. (Cited by 139 | Annotation | Google | Edit)

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 | Edit)

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 | Edit)

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 | Edit)

Fodor, Jerry A. (1989). Modules, frames, fridgeons, sleeping dogs. In Modularity in Knowledge Representation and Natural-Language Understanding. Cambridge: MIT Press. (Google | Edit)

Fodor, Jerry A. (1987). Modules, frames, fridgeons. In Modularity In Knowledge Representation And Natural-Language Understanding. Cambridge: Mit Press. (Google | Edit)

Haugeland, John (1987). An overview of the frame problem. In Zenon W. Pylyshyn (ed.), The Robot's Dilemma. Ablex. (Cited by 17 | Annotation | Google | Edit)

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 | Edit)

Hendricks, Scott (2006). The frame problem and theories of belief. Philosophical Studies 129 (2):317-33. (Google | More links | Edit)

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

Janlert, Lars-Erik (1987). Modeling change: The frame problem. In Zenon W. Pylyshyn (ed.), The Robot's Dilemma. Ablex. (Cited by 23 | Google | Edit)

Korb, Kevin B. (1998). The frame problem: An AI fairy tale. Minds and Machines 8 (3):317-351. (Cited by 1 | Google | More links | Edit)

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 | Edit)

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 | Edit)

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 | Edit)

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 | Edit)

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 | Edit)

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 | Edit)

Murphy, Dominic (2001). Folk psychology meets the frame problem. Studies in History and Philosophy of Modern Physics 32 (3):565-573. (Google | Edit)

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 | Edit)

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 | Edit)

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 | Edit)

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 | Edit)

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 | Edit)

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

6.4c	AI Methodology [32]

6.4e	Robotics [34]

2.1d	Beliefs

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