The goal of this work involves the developing of an argumentation-based formalism that an agent could use for constructing plans. In this formalism, agents will have certain knowledge about the world, and a set of actions that they will be…

A number of passages in the Satyricon reveal knowledge of Christianity, which Petronius can have acquired during his official duties in the eastern provinces.

In the last years there has been an increasing demand of a variety of logical systems, prompted
mostly by applications of logic in AI, logic programming and other related areas. Labeled Deductive
Systems (LDS) were developed as a °exible methodology…

Artificial Intelligence (AI) has long dealt with the issue of finding a suitable formalization for commonsense reasoning. Defeasible argumentation has proven to be a successful approach in many respects, proving to be a confluence point for many alternative logical frameworks.…

The design of intelligent agents is a key issue for many applications. Although there is no universally accepted de nition of intelligence, a notion of rational agency has been proposed as an alternative for the characterization of intelligent agency.
Modeling…

by Kah-Peng Aw., Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management, 2001., Includes bibliographical references (leaf 55).

We identify different kinds of relevance relations between formulas that emerge in the process of belief revision. Informal definitions for alternative notions of relevance are suggested and a set of schemas and intuitive postulates for formalizing these notions are proposed.

This paper presents an adaptive learning model for market-making under the reinforcement learning framework. Reinforcement learning is a learning technique in which agents aim to maximize the long-term accumulated rewards. No knowledge of the market environment, such as the order…

This thesis considers three complications that arise from applying reinforcement learning to a real-world application. In the process of using reinforcement learning to build an adaptive electronic market-maker, we find the sparsity of data, the partial observability of the domain,…

Humans recognize optical reflectance properties of surfaces such as metal, plastic, or paper from a single image without knowledge of illumination. We develop a machine vision system to perform similar recognition tasks automatically. Reflectance estimation under unknown, arbitrary illumination proves…