The Turing Test and the Zombie Argument

In this paper I shall try to put some implications concerning the Turing's test and the so-called Zombie arguments into the context of philosophy of mind. My intention is not to compose a review of relevant concepts, but to discuss central problems, which originate from the Turing's test - as a paradigm of computational theory of mind - with the arguments, which refute sustainability of this thesis. In the first section (Section I), I expose the basic computationalist presuppositions; by examining the premises of the Turing Test (TT) I argue that the TT, as a functionalist paradigm concept, underlies the computational theory of mind. I treat computationalism as a thesis that defines the human cognitive system as a physical, symbolic and semantic system, in such a manner that the description of its physical states is isomorphic with the description of its symbolic conditions, so that this isomorphism is semantically interpretable. In the second section (Section II), I discuss the Zombie arguments, and the epistemological-modal problems connected with them, which refute sustainability of computationalism. The proponents of the Zombie arguments build their attack on the computationalism on the basis of thought experiments with creatures behaviorally, functionally and physically indistinguishable from human beings, though these creatures do not have phenomenal experiences. According to the consequences of these thought experiments - if zombies are possible, then, the computationalism doesn't offer a satisfying explanation of consciousness. I compare my thesis from Section 1, with recent versions of Zombie arguments, which claim that computationalism fails to explain qualitative phenomenal experience. I conclude that despite the weaknesses of computationalism, which are made obvious by zombie-arguments, these arguments are not the last word when it comes to explanatory force of computationalism

Spartan Daily, March 21, 1974

Volume 62, Issue 23https://scholarworks.sjsu.edu/spartandaily/5846/thumbnail.jp

Spartan Daily, January 21, 1942

Volume 30, Issue 69https://scholarworks.sjsu.edu/spartandaily/3389/thumbnail.jp

Spartan Daily, January 21, 1942

Volume 30, Issue 69https://scholarworks.sjsu.edu/spartandaily/3389/thumbnail.jp

The New Basel Accord and the Nature of Risk: A Game Theoretic Perspective

Basel II changes risk management in banks strongly. Internal rating procedures would lead one to expect that banks are changing over to active risk control. But, if risk management is no longer a simple "game against nature", if all agents involved are active players then a shift from a non-strategic model setting (measuring event risk stochastically) to a more general strategic model setting (measuring behavioral risk adequately) comes true. Knowing that a game is any situation in which the players make strategic decisions – i.e., decisions that take into account each other's actions and responses – game theory is a useful set of tools for better understanding different risk settings. Embedded in a short history of the Basel Accord in this article we introduce some basic ideas of game theory in the context of rating procedures in accordance with Basel II. As well, some insight is given how game theory works. Here, the primary value of game theory stems from its focus on behavioral risk: risk when all agents are presumed rational, each attempting to anticipate likely actions and reactions by its rivals --New Basel Accord,event risk,behavioral risk,rating,simple game,Nash-equilibrium,game theory

Iowa State Daily (November 15, 2011)

Contents: Long road to success; Ames Library hosts global event; Students audition to strut down the runway; Cyclones breeze by Houston; Preparing for Drakehttps://lib.dr.iastate.edu/iowastatedaily_2011-11/1008/thumbnail.jp

Abalearn: a risk-sensitive approach to self-play learning in Abalone

This paper presents Abalearn, a self-teaching Abalone pro gram capable of automatically reaching an intermediate level of play without needing expert-labeled training examples, deep searches or ex posure to competent play. Our approach is based on a reinforcement learning algorithm that is risk seeking, since defensive players in Abalone tend to never end a game. We show that it is the risk-sensitivity that allows a successful self-play training. We also propose a set of features that seem relevant for achiev ing a good level of play. We evaluate our approach using a fixed heuristic opponent as a bench mark, pitting our agents against human players online and comparing samples of our agents at different times of training.info:eu-repo/semantics/publishedVersio

The Columns (1971 Dec 7)

Table of Contents: So, step aside..... New editors Faculty will discuss tenure policy Moody center planned Division II plots curriculum changes The Chess Board Student letters discuss gym, IRC White Gift Service Sunday Students raise relief moneyhttps://digitalcommons.hollins.edu/newspapers/2001/thumbnail.jp