Most automated theorem provers are clausal-form provers based on variants of resolutionrefutation. In my [1990], I described the theorem prover OSCAR that was based instead on natural deduction. Some limited evidence was given suggesting that OSCAR was suprisingly efficient. The evidence consisted of a handful of problems for which published data was available describing the performance of other theorem provers. This evidence was suggestive, but based upon too meager a comparison to be conclusive. The question remained, “How does natural deduction (...) compare with resolution-refutation?” In the ensuing seven years, OSCAR has evolved in important ways, and other developments have made it possible to collect more accurate comparative data. Specifically, the creation of the TPTP library of problems for theorem provers,1 and the availability of important theorem provers on the world wide web, make objective comparisons easier. These developments recently inspired Geoff Sutcliffe, one of the founders of the TPTP library, to issue a challenge to OSCAR. At CADE-13, a competition was held for clausal-form theorem provers.2 Otter was one of the most successful contestants. In addition, Otter is able to handle problems stated in natural form (as opposed to clausal form), and Otter is readily available for different platforms.3 Sutcliffe selected 212 problems from the TPTP library, and suggested that OSCAR and Otter run these problems on the same hardware. This “Shootout at the ATP corral” took place, with the result that OSCAR was on the average 40 times faster than Otter. In addition, OSCAR was able to find proofs for 16 problems on which Otter failed, and Otter was able to find proofs for 3 problems on which OSCAR failed. Taking into account that Otter was written in C and OSCAR in LISP, the speed difference of the algorithms themselves could be as much as an order of magnitude greater. Apparently, natural deduction has some advantages over resolution-refutation.. (shrink)

Epistemic defeat is standardly understood in either evidentialist or responsibilist terms. The seminal treatment of defeat is an evidentialist one, due to John Pollock, who famously distinguishes between undercutting and rebutting defeaters. More recently, an orthogonal distinction due to Jennifer Lackey has become widely endorsed, between so-called doxastic (or psychological) and normative defeaters. We think that neither doxastic nor normative defeaters, as Lackey understands them, exist. Both of Lackey’s categories of defeat derive from implausible assumptions about epistemic responsibility. (...) Although Pollock’s evidentialist view is superior, the evidentialism per se can be purged from it, leaving a general structure of defeat that can be incorporated in a reliabilist theory that is neither evidentialist nor responsibilist in any way. (shrink)

Reidel, 1976. This book is out of print, but can be downloaded as a pdf file (3.3 MB).

Reliabilist theories propose to analyse epistemic justification in terms of reliability. This paper argues that if we pay attention to the details of probability theory we find that there is no concept of reliability that can possibly play the role required by reliabilist theories. A distinction is drawn between the general reliability of a process and the single case reliability of an individual belief, And it is argued that neither notion can serve the reliabilist adequately.

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 (...) such non-descriptive “reflexive” designators is essential for making sophisticated cognition work in a general-purpose cognitive agent. If we were to build a robot capable of similar cognitive tasks as humans, it would have to be equipped with such designators. Once we understand the functional role of reflexive designators in cognition, we will see that to make cognition work properly, an agent must use a de se designator in specific ways in its reasoning. Rather simple arguments based upon how “I” works in reasoning lead to the conclusion that it cannot designate the body or part of the body. If it designates anything, it must be something non-physical. However, for the purpose of making the reasoning work correctly, it makes no difference whether “I” actually designates anything. If we were to build a robot that more or less duplicated human cognition, we would not have to equip it with anything for “I” to designate, and general physicalist inclinations suggest that there would be nothing for “I” to designate in the robot. In particular, it cannot designate the physical contraption. So the robot would believe “I exist”, but it would be wrong. Why should we think we are any different? (shrink)

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 (...) can help humans in these enterprises must make decisions and draw conclusions that are rational by human standards of rationality. Anthropomorphic agents can be contrasted with goal-oriented agents --” those that can carry out certain narrowly-defined tasks in the world. Here the objective is to get the job done, and it makes little difference how the agent achieves its design goal. (shrink)

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.

The objective of this paper is to construct an implementable theory of rational decision-making for cognitive agents subject to realistic resource constraints. It is argued that decision-making should select actions indirectly by selecting plans that prescribe them. It is also argued that although expected values provide the tool for evaluating plans, plans cannot be compared straightforwardly in terms of their expected values, and the objective of a realistic agent cannot be to find optimal plans. The theory of Locally Global planning (...) is proposed as a realistic alternative to standard "maximizing" theories of rational decision-making. (shrink)

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 (...) similar to its own, and that they have thoughts related to their rational architectures in certain ways. This leads to Rational Functionalism as an account of what it is to be a cognizer having mental states. That in turn entails that a computer can be a person in precisely the same sense as my next door neighbor if it can appropriately mimic my rational architecture. There is nothing I could know about my neighbor that I could not believe with equal justification about the computer. Rational Functionalism also makes it reasonable to define the narrow content of a thought to be its overall place in the agent's rational architecture, that is, its conceptual role. This is, however, avery narrow notion of content. For practical purposes, we are not interested in knowing the narrow contents of other people's thoughts. We are only interested in rather general properties of those narrow contents. This is what is expressed by the use ofthat-clauses in public language. (shrink)

When von Neumann's and Morgenstern's Theory of Games and Economic Behavior appeared in 1944, one thought that a complete theory of strategic social behavior had appeared out of nowhere. However, game theory has, to this very day, remained a fast-growing assemblage of models which have gradually been united in a new social theory - a theory that is far from being completed even after recent advances in game theory, as evidenced by the work of the three Nobel Prize winners, (...) class='Hi'>John F. Nash, John C. Harsanyi, and Reinhard Selten. Two of them, Harsanyi and Selten, have contributed important articles to the present volume. This book leaves no doubt that the game-theoretical models are on the right track to becoming a respectable new theory, just like the great theories of the twentieth century originated from formerly separate models which merged in the course of decades. For social scientists, the age of great discover ies is not over. The recent advances of today's game theory surpass by far the results of traditional game theory. For example, modem game theory has a new empirical and social foundation, namely, societal experiences; this has changed its methods, its "rationality. " Morgenstern (I worked together with him for four years) dreamed of an encompassing theory of social behavior. With the inclusion of the concept of evolution in mathematical form, this dream will become true. Perhaps the new foundation will even lead to a new name, "conflict theory" instead of "game theory. (shrink)

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, (...) the search for optimal plans is completely intractable. An alternative theory of rational decision making is proposed, called “locally global planning”. (shrink)

This technical report describes the construction of an experimental planner that finds plans by reasoning about them defeasibly rather than by running a search algorithm. The need for such a planner is defended in the paper “The Logical Foundations of Goal-Regression Planning”.

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.