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  1. Jenann Ismael & John L. Pollock, So You Think You Exist? — In Defense of Nolipsism.
    Human beings think of themselves in terms of a privileged non-descriptive designator — a mental “I”. Such thoughts are called “de se” thoughts. The mind/body problem is the problem of deciding what kind of thing I am, and it can be regarded as arising from the fact that we think of ourselves non-descriptively. Why do we think of ourselves in this way? We investigate the functional role of “I” (and also “here” and “now”) in cognition, arguing that the use of (...)
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  2. John L. Pollock, An Easy “Hard Problem” for Decision-Theoretic Planning.
    This paper presents a challenge problem for decision-theoretic planners. State-space planners reason globally, building a map of the parts of the world relevant to the planning problem, and then attempt to distill a plan out of the map. A planning problem is constructed that humans find trivial, but no state-space planner can solve. Existing POCL planners cannot solve the problem either, but for a less fundamental reason.
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  3. John L. Pollock, Against Optimality: Logical Foundations for Decision-Theoretic Planning in Autonomous Agents.
    This paper investigates decision-theoretic planning in sophisticated autonomous agents operating in environments of real-world complexity. An example might be a planetary rover exploring a largely unknown planet. It is argued th a t existing algorithms for decision-theoretic planning are based on a logically incorrect theory of rational decision making. Plans cannot be evaluated directly in terms of their expected values, because plans can be of different scopes, and they can interact with other previously adopted plans. Furthermore, in the real world, (...)
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  4. John L. Pollock, Epistemology: Five Questions.
    As a high school student, I rediscovered Hume’s problem of induction on my own. For a while, I was horrified. I thought, “We cannot know anything!” After a couple of weeks I calmed down and reasoned that there had to be something wrong with my thinking, and that led me quickly to the realization that good reasons need not be deductive, and to the discovery of defeasible reasoning. From there it was a short jump to a more general interest in (...)
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  5. John L. Pollock, Locally Global Planning.
    It is conjectured that MDP and POMDP planning will remain unfeasible for complex domains, so some form of ÒclassicalÓ decision-theoretic planning is sought. However, local plans cannot be properly compared in terms of their expected values, because those values will be affected by the other plans the agent has adopted. Plans must instead be merged into a single Òmaster-planÓ, and new plans evaluated in terms of their contribution to the value of the master plan. To make both the construction and (...)
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  6. John L. Pollock, Probabilities for AI.
    Probability plays an essential role in many branches of AI, where it is typically assumed that we have a complete probability distribution when addressing a problem. But this is unrealistic for problems of real-world complexity. Statistical investigation gives us knowledge of some probabilities, but we generally want to know many others that are not directly revealed by our data. For instance, we may know prob(P/Q) (the probability of P given Q) and prob(P/R), but what we really want is prob(P/Q&R), and (...)
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  7. John L. Pollock, Part One: Virtual Machines.
    It’s morning. You sit down at your desk, cup of coffee in hand, and prepare to begin your day. First, you turn on your computer. Once it is running, you check your e-mail. Having decided it is all spam, you trash it. You close the window on your e-mail program, but leave the program running so that it will periodically check the mail server to see whether you have new mail. If it finds new mail it will alert you by (...)
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  8. John L. Pollock, Thinking About Acting.
    The objective of this book is to produce a theory of rational decision making for realistically resource-bounded agents. My interest is not in “What should I do if I were an ideal agent?”, but rather, “What should I do given that I am who I am, with all my actual cognitive limitations?” The book has three parts. Part One addresses the question of where the values come from that agents use in rational decision making. The most comon view among philosophers (...)
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  9. John L. Pollock, The Need for an Epistemology.
    It is argued that we cannot build a sophisticated autonomous planetary rover just by implementing sophisticated planning algorithms. Planning must be based on information, and the agent must have the cognitive capability of acquiring new information about its environment. That requires the implementation of a sophisticated epistemology. Epistemological considerations indicate that the rover cannot be assumed to have a complete probability distribution at its disposal. Its planning must be based upon “thin” knowledge of probabilities, and that has important implications for (...)
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  10. John L. Pollock, Language and Thought.
    Princeton University Press, 1982. This book is out of print, but can be downloaded as a pdf file (5 MB).
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  11. John L. Pollock, Problems for Bayesian Epistemology.
    In the past, few mainstream epistemologists have endorsed Bayesian epistemology, feeling that it fails to capture the complex structure of epistemic cognition. The defenders of Bayesian epistemology have tended to be probability theorists rather than epistemologists, and I have always suspected they were more attracted by its mathematical elegance than its epistemological realism. But recently Bayesian epistemology has gained a following among younger mainstream epistemologists. I think it is time to rehearse some of the simpler but still quite devastating objections (...)
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  12. John L. Pollock (forthcoming). Chisholm on States of Affairs. Grazer Philosophische Studien 7:163-175.
    Chisholm's ontological objective is the reductionist one of translating statements which appear to be about propositions and generic events into statements about states of affairs, denying the existence of concrete events altogether. The paper questions this program by criticising the notion of concretization on which Chisholm heavily relies. It is argued that there are no convincing arguments in favor of eliminative reductionism. Translability of statements about one kind of entity into statements about another kind of entity has nothing to do (...)
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  13. John L. Pollock (2012). Oscar. Journal of Applied Non-Classical Logics 6 (1):89-113.
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  14. John L. Pollock (2010). A Resource-Bounded Agent Addresses the Newcomb Problem. Synthese 176 (1):57 - 82.
    In the Newcomb problem, the standard arguments for taking either one box or both boxes adduce what seem to be relevant considerations, but they are not complete arguments, and attempts to complete the arguments rely upon incorrect principles of rational decision making. It is argued that by considering how the predictor is making his prediction, we can generate a more complete argument, and this in turn supports a form of causal decision theory.
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  15. John L. Pollock (2010). 10 Reasoning Defeasibly About Probabilities. In Joseph Keim Campbell, Michael O.’Rourke & Harry S. Silverstein (eds.), Knowledge and Skepticism. Mit Press. 219.
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  16. John L. Pollock (2008). Irrationality and Cognition. In Quentin Smith (ed.), Epistemology: New Essays. Oxford University Press.
    The strategy of this paper is to throw light on rational cognition and epistemic justification by examining irrationality. Epistemic irrationality is possible because we are reflexive cognizers, able to reason about and redirect some aspects of our own cognition. One consequence of this is that one cannot give a theory of epistemic rationality or epistemic justification without simultaneously giving a theory of practical rationality. A further consequence is that practical irrationality can affect our epistemic cognition. I argue that practical irrationality (...)
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  17. John L. Pollock (2008). What Am I? Philosophy and Phenomenological Research 76 (2):237-309.
    It’s morning. You sit down at your desk, cup of coffee in hand, and prepare to begin your day. First, you turn on your computer. Once it is running, you check your e-mail. Having decided it is all spam, you trash it. You close the window on your e-mail program, but leave the program running so that it will periodically check the mail server to see whether you have new mail. If it finds new mail it will alert you by (...)
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  18. John L. Pollock (2008). What Am I? Virtual Machines and the Mind/Body Problem. Philosophy and Phenomenological Research 76 (2):237–309.
    When your word processor or email program is running on your computer, this creates a "virtual machine” that manipulates windows, files, text, etc. What is this virtual machine, and what are the virtual objects it manipulates? Many standard arguments in the philosophy of mind have exact analogues for virtual machines and virtual objects, but we do not want to draw the wild metaphysical conclusions that have sometimes tempted philosophers in the philosophy of mind. A computer file is not made of (...)
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  19. John L. Pollock & Jenann Ismael (2006). So You Think You Exist? — In Defense of Nolipsism. In Thomas M. Crisp, Matthew Davidson & David Vander Laan (eds.), Knowledge and Reality: Essays in Honor of Alvin Plantinga. Springer.
    Human beings think of themselves in terms of a privileged non-descriptive designator — a mental “I”. Such thoughts are called “_de se_” thoughts. The mind/body problem is the problem of deciding what kind of thing I am, and it can be regarded as arising from the fact that we think of ourselves non-descriptively. Why do we think of ourselves in this way? We investigate the functional role of “I” (and also “here” and “now”) in cognition, arguing that the use of (...)
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  20. John L. Pollock & Iris Oved (2005). Vision, Knowledge, and the Mystery Link. Noûs 39 (1):309-351.
    Imagine yourself sitting on your front porch, sipping your morning coffee and admiring the scene before you. You see trees, houses, people, automobiles; you see a cat running across the road, and a bee buzzing among the flowers. You see that the flowers are yellow, and blowing in the wind. You see that the people are moving about, many of them on bicycles. You see that the houses are painted different colors, mostly earth tones, and most are one-story but a (...)
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  21. John L. Pollock (2002). Causal Probability. Synthese 132 (1-2):143 - 185.
    Examples growing out of the Newcomb problem have convinced many people that decision theory should proceed in terms of some kind of causal probability. I endorse this view and define and investigate a variety of causal probability. My definition is related to Skyrms' definition, but proceeds in terms of objective probabilities rather than subjective probabilities and avoids taking causal dependence as a primitive concept.
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  22. John L. Pollock (2002). Rational Choice and Action Omnipotence. Philosophical Review 111 (1):1-23.
    Counterexamples are constructed for the theory of rational choice that results from a direct application of classical decision theory to ordinary actions. These counterexamples turn on the fact that an agent may be unable to perform an action, and may even be unable to try to perform an action. An alternative theory of rational choice is proposed that evaluates actions using a more complex measure, and then it is shown that this is equivalent to applying classical decision theory to "conditional (...)
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  23. John L. Pollock (2002). The Logical Foundations of Means-End Reasoning. In Renée Elio (ed.), Common Sense, Reasoning, & Rationality. Oxford University Press. 60.
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  24. John L. Pollock (2001). Evaluative Cognition. Noûs 35 (3):325–364.
    Cognitive agents form beliefs representing the world, evaluate the world as represented, form plans for making the world more to their liking, and perform actions executing the plans. Then the cycle repeats. This is the doxastic-conative loop, diagrammed in figure one.1 Both human beings and the autonomous rational agents envisaged in AI are cognitive agents in this sense. The cognition of a cognitive agent can be subdivided into two parts. Epistemic cognition is that kind of cognition responsible for producing and (...)
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  25. Richard Fumerton, Laurence Bonjour, John L. Pollock & Alvin Plantinga (2000). Resurrecting Old-Fashioned Foundationalism. Rowman & Littlefield Publishers.
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  26. John L. Pollock (2000). Rationality in Philosophy and Artificial Intelligence. In The Proceedings of the Twentieth World Congress of Philosophy, Volume 9: Philosophy of Mind. Charlottesville: Philosophy Doc Ctr. 123-132.
    I argue here that sophisticated AI systems, with the exception of those aimed at the psychological modeling of human cognition, must be based on general philosophical theories of rationality and, conversely, philosophical theories of rationality should be tested by implementing them in AI systems. So the philosophy and the AI go hand in hand. I compare human and generic rationality within a broad philosophy of AI and conclude by suggesting that ultimately, virtually all familiar philosophical problems will turn out to (...)
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  27. John L. Pollock (2000). The Proceedings of the Twentieth World Congress of Philosophy, Volume 9: Philosophy of Mind. Charlottesville: Philosophy Doc Ctr.
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  28. John L. Pollock & Anthony S. Gillies (2000). Belief Revision and Epistemology. Synthese 122 (1-2):69-92.
    Postulational approaches attempt to understand the dynamics of belief revision by appealing to no more than the set of beliefs held by an agent and the logical relations between them. It is argued there that such an approach cannot work. A proper account of belief revision must also appeal to the arguments supporting beliefs, and recognize that those arguments can be defeasible. If we begin with a mature epistemological theory that accommodates this, it can be seen that the belief revision (...)
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  29. John L. Pollock (1999). Rational Cognition in Oscar. Agent Theories.
    Stuart Russell [14] describes rational agents as --œthose that do the right thing--�. The problem of designing a rational agent then becomes the problem of figuring out what the right thing is. There are two approaches to the latter problem, depending upon the kind of agent we want to build. On the one hand, anthropomorphic agents are those that can help human beings rather directly in their intellectual endeavors. These endeavors consist of decision making and data processing. An agent that (...)
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  30. John L. Pollock, The Oscar Project.
    The objective of the OSCAR Project is twofold. On the one hand, it is to construct a general theory of rational cognition. On the other hand, it is to construct an artificial rational agent (an "artilect") implementing that theory. This is a joint project in philosophy and AI.
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  31. John L. Pollock (1997). Reasoning About Change and Persistence: A Solution to the Frame Problem. Noûs 31 (2):143-169.
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  32. John L. Pollock (1995). Cognitive Carpentry. Mit Press.
    "A sequel to Pollock's How to Build a Person, this volume builds upon that theoretical groundwork for the implementation of rationality through artificial ...
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  33. John L. Pollock (1995). Practical Reasoning in Oscar. Philosophical Perspectives 9:15-48.
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  34. John L. Pollock (1994). Foundations for Direct Inference. Theory and Decision 17 (3):221-255.
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  35. John L. Pollock (1993). The Phylogeny of Rationality. Cognitive Science 17 (4):563-588.
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  36. Robert C. Cummins & John L. Pollock (eds.) (1992). Philosophy and AI: Essays at the Interface. MIT Press.
    Philosophy and AI presents invited contributions that focus on the different perspectives and techniques that philosophy and AI bring to the theory of ...
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  37. John L. Pollock (1992). New Foundations for Practical Reasoning. Minds and Machines 2 (2):113-144.
    Practical reasoning aims at deciding what actions to perform in light of the goals a rational agent possesses. This has been a topic of interest in both philosophy and artificial intelligence, but these two disciplines have produced very different models of practical reasoning. The purpose of this paper is to examine each model in light of the other and produce a unified model adequate for the purposes of both disciplines and superior to the standard models employed by either.The philosophical (decision-theoretic) (...)
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  38. John L. Pollock (1992). Rationality, Function, and Content. Philosophical Studies 65 (1-2):129-151.
    To summarize, in order for rational agents to be able to engage in the sophisticated kinds of reasoning exemplified by human beings, they must be able to introspect much of their cognition. The problem of other minds and the problem of knowing the mental states of others will arise automatically for any rational agent that is able to introspect its own cognition. The most that a rational agent can reasonably believe about other rational agents is that they have rational architectures (...)
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  39. John L. Pollock (1992). Reply to Shope. Philosophy and Phenomenological Research 52 (2):411-413.
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  40. John L. Pollock (1992). The Theory of Nomic Probability. Synthese 90 (2):263 - 299.
    This article sketches a theory of objective probability focusing on nomic probability, which is supposed to be the kind of probability figuring in statistical laws of nature. The theory is based upon a strengthened probability calculus and some epistemological principles that formulate a precise version of the statistical syllogism. It is shown that from this rather minimal basis it is possible to derive theorems comprising (1) a theory of direct inference, and (2) a theory of induction. The theory of induction (...)
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  41. John L. Pollock (1991). How to Use Probabilities in Reasoning. Philosophical Studies 64 (1):65 - 85.
    Probabilities are important in belief updating, but probabilistic reasoning does not subsume everything else (as the Bayesian would have it). On the contrary, Bayesian reasoning presupposes knowledge that cannot itself be obtained by Bayesian reasoning, making generic Bayesianism an incoherent theory of belief updating. Instead, it is indefinite probabilities that are of principal importance in belief updating. Knowledge of such indefinite probabilities is obtained by some form of statistical induction, and inferences to non-probabilistic conclusions are carried out in accordance with (...)
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  42. John L. Pollock (1991). Self-Defeating Arguments. Minds and Machines 1 (4):367-392.
    An argument is self-defeating when it contains defeaters for some of its own defeasible lines. It is shown that the obvious rules for defeat among arguments do not handle self-defeating arguments correctly. It turns out that they constitute a pervasive phenomenon that threatens to cripple defeasible reasoning, leading to almost all defeasible reasoning being defeated by unexpected interactions with self-defeating arguments. This leads to some important changes in the general theory of defeasible reasoning.
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  43. John L. Pollock (1990). Nomic Probability and the Foundations of Induction. Oxford University Press.
    In this book Pollock deals with the subject of probabilistic reasoning, making general philosophical sense of objective probabilities and exploring their ...
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  44. John L. Pollock (1990). Philosophy and Artificial Intelligence. Philosophical Perspectives 4:461-498.
  45. John L. Pollock (1990). Technical Methods in Philosophy. Westview Press.
     
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  46. John L. Pollock (1990). Understanding the Language of Thought. Philosophical Studies 58 (1-2):95-120.
    The author poses a question: when a person has a thought, what is it that determines what thought he is having? and, equivalently, what is it that determines what thought he is having. looking for an answer he sketches some general aspects of the problems involved in answering these questions, like the mind/body problem, for example. his conclusion is that the posed questions should be set against the background assumption that thoughts are just internal physical occurrences, and that thoughts are (...)
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  47. John L. Pollock (1989). How to Build a Person: A Prolegomenon. MIT Press.
    Pollock describes an exciting theory of rationality and its partial implementation in OSCAR, a computer system whose descendants will literally be persons.
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  48. John L. Pollock (1988). Interest-Driven Reasoning. Synthese 74 (3):369 - 390.
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  49. John L. Pollock (1988). My Brother, the Machine. Noûs 22 (June):173-211.
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  50. John L. Pollock (1988). The Building of Oscar. Philosophical Perspectives 2:315-344.
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