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Jonathan Wilkenfeld

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5 papers

2 author rows

AIJ Journal 2008 Journal Article

Negotiating with bounded rational agents in environments with incomplete information using an automated agent

Raz Lin
Sarit Kraus
Jonathan Wilkenfeld
James Barry

Many tasks in day-to-day life involve interactions among several people. Many of these interactions involve negotiating over a desired outcome. Negotiation in and of itself is not an easy task, and it becomes more complex under conditions of incomplete information. For example, the parties do not know in advance the exact tradeoff of their counterparts between different outcomes. Furthermore information regarding the preferences of counterparts might only be elicited during the negotiation process itself. In this paper we propose a model for an automated negotiation agent capable of negotiating with bounded rational agents under conditions of incomplete information. We test this agent against people in two distinct domains, in order to verify that its model is generic, and thus can be adapted to any domain as long as the negotiators' preferences can be expressed in additive utilities. Our results indicate that the automated agent reaches more agreements and plays more effectively than its human counterparts. Moreover, in most of the cases, the automated agent achieves significantly better agreements, in terms of individual utility, than the human counterparts playing the same role.

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AIJ Journal 2008 Journal Article

Resolving crises through automated bilateral negotiations

Sarit Kraus
Penina Hoz-Weiss
Jonathan Wilkenfeld
David R. Andersen
Amy Pate

We describe the development of an automated agent that can negotiate efficiently with people in crises. The environment is characterized by two negotiators, time constraints, deadlines, full information, and the possibility of opting out. The agent can play either role, with communications via a pre-defined language. The model used in constructing the agent is based on a formal analysis of the crises scenario using game-theoretic methods and heuristics for bargaining. The agent receives messages sent by its opponent, analyzes them and responds. It also initiates discussion on one or more parameters of an agreement. Experimental results of simulations of a fishing dispute between Canada and Spain indicate that the agent played at least as well as, and in the case of Spain, significantly better than a human player.

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IS Journal 2007 Journal Article

CARA: A Cultural-Reasoning Architecture

V.S. Subrahmanian
Massimiliano Albanese
Maria Vanina Martinez
Dana Nau
Diego Reforgiato
Gerardo I. Simari
Amy Sliva
Jonathan Wilkenfeld

There's a constant need to reason about diverse cultures all over the world. Past cultural-reasoning research has focused primarily on techniques to organize, catalog, and reason about cultural and historical artifacts of the kind typically stored in a museum. This is extremely valuable. However, the term "cultural reasoning" as we use it in the previous examples (and in this article) focuses on understanding how different cultural groups today make decisions and what factors those decisions are based on. An architecture that supports cultural reasoning should, for example, be able to pinpoint characteristics that differentiate organizations engaging political action within legitimate frameworks from those engaging in violence and terror. Key in all this is that cultural reasoning must go hand in hand with environmental reasoning. We believe that any architecture to support cultural reasoning about a given group, political entity, business, or religious organization should contain these components: 1) a semantic Web extraction engine to elicit data about the organization, 2) an opinion-mining engine that captures the organization's opinions, 3) an algorithm to correlate environmental variables with actions that the organization takes, and 4) a simulation or game environment within which analysts and users can see what the organization has done and what it might do in hypothetical situations

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ECAI Conference 2006 Conference Paper

An Automated Agent for Bilateral Negotiation with Bounded Rational Agents with Incomplete Information

Raz Lin
Sarit Kraus
Jonathan Wilkenfeld
James Barry

Many day-to-day tasks require negotiation, mostly under conditions of incomplete information. In particular, the opponent's exact tradeoff between different offers is usually unknown. We propose a model of an automated negotiation agent capable of negotiating with a bounded rational agent (and in particular, against humans) under conditions of incomplete information. Although we test our agent in one specific domain, the agent's architecture is generic; thus it can be adapted to any domain as long as the negotiators' preferences can be expressed in additive utilities. Our results indicate that the agent played significantly better, including reaching a higher proportion of agreements, than human counterparts when playing one of the sides, while when playing the other side there was no significant difference between the results of the agent and the human players.

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AIJ Journal 1995 Journal Article

Multiagent negotiation under time constraints

Sarit Kraus
Jonathan Wilkenfeld
Gilad Zlotkin

Research in distributed artificial intelligence (DAI) is concerned with how automated agents can be designed to interact effectively. Negotiation is proposed as a means for agents to communicate and compromise to reach mutually beneficial agreements. The paper examines the problems of resource allocation and task distribution among autonomous agents which can benefit from sharing a common resource or distributing a set of common tasks. We propose a strategic model of negotiation that takes the passage of time during the negotiation process itself into account. A distributed negotiation mechanism is introduced that is simple, efficient, stable, and flexible in various situations. The model considers situations characterized by complete as well as incomplete information, and ones in which some agents lose over time while others gain over time. Using this negotiation mechanism autonomous agents have simple and stable negotiation strategies that result in efficient agreements without delays even when there are dynamic changes in the environment.

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