The paper exposits a number of key dynamic models from the field of economics. The models share the feature that evolution of the system is consistent with the optimizing behavior of rational economic agents. Specifically, the laws of motion that we investigate are solutions to discrete time dynamic decision processes. Even with rational agents and simple economic environments, a variety of com...

We introduce a new probabilistic approach to dealing with uncertainty, based on the observation that probability theory does not require that every event be assigned a probability. For a nonmeasurable event (one to which we do not assign a probability), we can talk about only the inner measure and outer measure of the event. Thus, the measure of belief in an event can be represented by an inter...

We introduce and study a unified reasoning process which allows to represent the beliefs of both a fully rational agent and an unaware one. This reasoning process endows introspection and unawareness with natural properties. The corresponding model for the rational or boundedly rational agents is easy both to describe and to work with, and the agent’s full system of beliefs has natural descript...

In this paper I outline an attempt to reconcile the traditional Artii-cial Intelligence notion of a logic-based rational agent with the contrary notion of a reactive agent that acts \instinctively" in response to conditions that arise in its environment. For this purpose, I will use the tools of meta-logic programming to deene the observation-thought-action cycle of an agent that combines the a...

This paper presents and discusses a novel approach to indeterministic belief revision. An indeterministic belief revision operator assumes that, when an agent is confronted with a new piece of information, it can revise its belief sets in more than one way. We define a rational agent not only in terms of what it believes but also of what it desires and wants to achieve. Hence, we propose that t...

We argue that none of the existing epistemic logics can adequately serve the needs of agent theories. We suggest a new concept of knowledge which generalizes both implicit and explicit knowledge and argue that this is the notion we need to formalize agents in Distributed Arti cial Intelligence. A logic of the new concept is developed which is formally and practically adequate in the following s...

Agents plan in order to improve their performance. However, planning takes time and consumes resources that may in fact degrade an agents performance. Ideally, an agent should only plan when the expected improvement outweighs the expected cost and no resources should be expended on making this decision. To do this, an agent would have to be omniscient. The problem of how to approximate this ide...

Whenever rational agents form coalitions to execute tasks, doing so via a decentralized negotiation process—while more robust and democratic—may lead to a loss of efficiency compared to a centralized solution. To quantify this loss, we introduce the notion of the Price of Democracy (PoD), which measures the amount of resources needlessly committed to the task(s) at hand. After defining this con...

This paper explores principles governing the rational balance among an agent's beliefs, goals, actions, and intentions. Such principles provide specifications for artificial agents, and approximate a theory of human action (as philosophers use the term). By making explicit the conditions under which an agent can drop his goals, i.e., by specifying how the agent is committed to his goals, the fo...

A population of fully rational agents play a symmetric 2-player game in biological fitnesses, but each agent’s play is determined by his payoffs, which are free to evolve according to “survival of the fittest” pressures. An equilibrium-selection mechanism is assumed to exist, and deliver a unique outcome for any given profile of payoffs; this allows the evolution of payoffs to be modeled as a w...