Language, Cognition, and Computation Lecture Series WHAT: Gary Drescher: "Newcomb's Problem and Deterministic Choice: Implications for Cognitive Design" WHEN: Friday, May 28, 2004, 3:00 PM EST WHERE: Bartos Theatre, MIT Media Lab (E15) HOSTED BY: Deb Roy AT&T Career Development Professor of Media Arts and Sciences Cognitive Machines group SUMMARY: Newcomb's Problem, a long-standing decision-theoretic paradox, posits an imaginary situation in which a simulator can reliably predict your actions. A large reward was previously irrevocably set up for you if and only if the simulator's prediction was that you would now make a choice which (apart from the large reward) is slightly unfavorable to you. A dilemma arises as to whether to make the choice that (almost certainly) implies that you reap the large reward, even though the choice does not cause your obtaining that reward. The paradox bears on the compatibility of choice and determinism, a quintessentially philosophical problem. But it also has important ramifications for the science and engineering of cognition. Newcomb's Problem illuminates a fundamental controversy about the foundations of decision theory, which translates into a central question about the design of intelligent, choice-making agents. What sort of relation between contemplated action and goal—causal, subjunctive, evidential, or some other relation—must hold for it to be sensible to consider the action a means to the goal? That is, what constitutes a means-end relation? And how might an agent that learns independently recognize when this relation holds? By appeal to relatively mundane, uncontroversial scenarios, Drescher argues against evidential and causal criteria for linking means to ends, and proposes instead a subjunctive criterion: an agent acts for the sake of what would be the case if this or that action were taken, which (he argues) is sometimes distinct from what an action either causes or gives evidence of. Drescher sketches a computational implementation of subjunctive means-end recognition, and shows how the proposed mechanism might resolve Newcomb's Problem. BIO: Gary Drescher received his PhD at the MIT AI Lab. His dissertation proposed empirical-learning and concept-inventing machinery to account for aspects of Piagetian cognitive development during infancy. Drescher is the author of Made-Up Minds: A Constructivist Approach to Artificial Intelligence. Now indulging in amateur philosophy, he is a visiting fellow at the Center for Cognitive Studies at Tufts. MIT Media Laboratory Home Page | Events Main Index