This paper presents a high-level framework for analysing and designing intelligent agents. The framework's key abstraction mechanism is a new computer level called the Social Level. The Social Level sits immediately above the Knowledge Level, as defined by Allen Newell, and is concerned with the inherently social aspects of multiple agent systems. To illustrate the working of this framework, an important new class of agent is identified and then specified. Socially responsible agents retain their local autonomy but still draw from, and provide resources to, the larger community. Through empirical evaluation, it is shown that such agents produce both good system-wide performance and good individual performance. 1. INTRODUCTION The number of multi-agent systems being designed and built is rapidly increasing as software agents gain acceptance as a powerful and useful technology for solving complex problems (Chaib-draa, 1995; Jennings, 1994; PAAM, 1996). As applications become more comple...

We address the issue of rational communicative behavior among autonomous self-interested agents that have to make decisions as to what to communicate, to whom, and how. Following decision theory, we postulate that a rational speaker should design a speech act so as to optimize the benefit it obtains as the result of the interaction. We quantify the gain in the quality of interaction in terms of the expected utility, and we present a framework that allows an agent to compute the expected utilities of various communicative actions. Our framework uses the Recursive Modeling Method as the specialized representation used for decision-making in a multi-agent environment. This representation includes information about the agent's state of knowledge, including the agent's preferences, abilities and beliefs about the world, as well as the beliefs the agent has about the other agents, the beliefs it has about the other agents' beliefs, and so on. Decision-theoretic pragmatics of a comm...

A satisfactory complete normative criterion for individualistic ethical decision-making under uncertainty such as Harsanyi’s (Journal of Political Economy, 1955) requires a single fundamental utility function for all individuals which is fully in-terpersonally comparable. The paper discusses reasons why interpersonal com-parisons of utility (ICU’s) have been eschewed in the past and argues that most existing approaches, both empirical and ethical, to ICU’s are flawed. Either they confound facts with values, or they are based on unrealistic hypothetical decisions in an “original position”. Instead ICU’s need to be recognized for what they really are — preferences for different kinds of people. INTERPERSONAL COMPARISONS OF UTILITY...I still believe that it is helpful to speak as if inter-personal comparisons of utility rest upon scientiÆcfoundations – that is, upon observation or introspection....I still think, when I make interpersonal comparisons... that my judgments are more like judgments of value than judgments of veriÆablefact. Nevertheless, to those of my friends who think differently, I would urge that, in practice, our difference is not very important. They think that propositions based upon the assumption of equality are essentially part of economic science. I think that the assumption of equality comes from outside, and that its justiÆcation is more ethical than scientiÆc.But we all agree that it is Ætting that such assumptions should be made and their implications explored with the aid of the economist’s technique.

Harsanyi’s utilitarian theorem states that the social welfare function is the weighted sum of individuals ’ utility functions if: (i) society maximizes expected social welfare; (ii) individuals maximize expected utility; (iii) society is indifferent between two probability distributions over social states whenever all individuals are. After giving a simpler proof, an alternative axiomatic foundation for Vickrey-Harsanyi utilitarianism is provided. By making using an extended version of Harsanyi’s concept of a player’s “type ” in the theory of games with incomplete information, the problem of forming social objectives when there is incomplete information can also be resolved, at least in principle.

As is the case with traditional markets, the sellers on the Internet do not usually know the demand functions of their customers. However, in such a digital environment, a seller can experiment different prices in order to maximize his profits. In this paper, we fit the dynamic pricing model of Rothschild [11] to match the pricing problem of a Web-store. In this setting, we define the optimization problem of a Web-store and by simulations we study the price dynamics that can appear when all the sellers on a given market follow an optimal pricing policy.

Drawing on on our work in the area of Distributed Artificial Intelligence, we propose the rudiments of a view of multiagent reasoning that relates current philosophical intuitions, theoretical foundations, and preliminary implementation. The philosophical position we take is a combination of Daniel Dennett's philosophy of the ladder of personhood (consisting of rationality, intentionality, stance, reciprocity, communication, and consciousness) on one hand, and the utilitarian philosophy of selfish utility maximization on the other hand. The theories we incorporate are logics of knowledge and belief, which in addressing the multiagent issues can be developed based on a recursive version of the Kripke structure, and the related fields of utility, decision and game theories. Our preliminary implementation, the Recursive Modeling Method (RMM), lets an agent coordinate its actions with the actions of other agents, cooperate with them when appropriate, and rationally choose an optimal form o...