Negotiation in a non-cooperative environment

Kraus, Sarit; Ephrati, Eithan; Lehmann, Daniel

doi:10.1080/09528139108915294

Cited by 27 publications

(11 citation statements)

References 6 publications

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“…To promote its interests, each can reason about the other agents' knowledge and goals. In some scenarios, agents have conflicting goals, negotiate, and compete over resources (Kraus, Ephrati, and Lehmann 1991;Zlotkin and Rosenschein 1991).…”

Section: Multiagent Planningmentioning

confidence: 99%

Planning to please: Following another agent's intended plan

Ephrati

Rosenschein

1993

Group Decis Negot

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In this article we analyze a particular model of control among intelligent agents, that of nonabsolute control. Non-absolute control involves a "supervisor" agent that issues orders to a "subordinate" agent. An example might be a human agent on Earth directing the activities of a Mars-based semi-autonomous vehicle.Both agents operate with essentially the same goals. The subordinate agent, however, is assumed to have access to some information that the supervisor does not have. The agent is thus expected to exercise its judgment in following orders (i.e., following the true intent of the supervisor, to the best of its ability). After presenting our model, we discuss the planning problem: how would a subordinate agent choose among alternative plans? Our solutions focus on evaluating the distance between candidate plans, and is appropriate to any scenario in which one agent wants to follow (as much as possible) another agent's plan.

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Section: Multiagent Planningmentioning

confidence: 99%

Planning to please: Following another agent's intended plan

Ephrati

Rosenschein

1993

Group Decis Negot

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“…An agent can negotiate in a non-cooperative environment to compete with each other for rewards [12,13]. Agents can also negotiate in fully prescribed manner where the negotiating parties know exactly what each other's cost and utility functions are, or when such knowledge is learned during the first step of interaction in a negotiation [14,15].…”

Section: Related Workmentioning

confidence: 99%

Sensor Web coalition formation via argumentation-based negotiation

Tsatsoulis

Amthauer

2009

2009 IEEE Aerospace Conference

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“…Negotiation has been a subject of central interest in DAI, as it has been in economics and political science (Rai a, 1982). The word has been used in a variety of ways, though in general it refers to communication processes that further coordination (Smith, 1978;Lesser & Corkill, 1981;Kuwabara & Lesser, 1989;Conry et al, 1988;Kreifelts & von Martial, 1991;Kraus, Ephrati, & Lehmann, 1991). These negotiating procedures have included the exchange of Partial Global Plans (Durfee, 1988;Durfee & Lesser, 1989), the communication of information intended to alter other agents' goals (Sycara, 1988(Sycara, , 1989, and the use of incremental suggestions leading to joint plans of action (Kraus & Wilkenfeld, 1991).…”

Section: Negotiationmentioning

confidence: 99%

Mechanisms for Automated Negotiation in State Oriented Domains

Zlotkin¹,

Rosenschein

1996

jair

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This paper lays part of the groundwork for a domain theory of negotiation, that is, a way of classifying interactions so that it is clear, given a domain, which negotiation mechanisms and strategies are appropriate. We de ne State Oriented Domains, a general category of interaction. Necessary and su cient conditions for cooperation are outlined. We use the notion of worth in an altered de nition of utility, thus enabling agreements in a wider class of joint-goal reachable situations. An approach is o ered for con ict resolution, and it is shown that even in a con ict situation, partial cooperative steps can be taken by interacting agents (that is, agents in fundamental con ict might still agree to cooperate up to a certain point).A Uni ed Negotiation Protocol (UNP) is developed that can be used in all types of encounters. It is shown that in certain borderline cooperative situations, a partial cooperative agreement (i.e., one that does not achieve all agents' goals) might be preferred by all agents, even though there exists a rational agreement that would achieve all their goals.Finally, we analyze cases where agents have incomplete information on the goals and worth of other agents. First we consider the case where agents' goals are private information, and we analyze what goal declaration strategies the agents might adopt to increase their utility. Then, we consider the situation where the agents' goals (and therefore standalone costs) are common knowledge, but the worth they attach to their goals is private information. We introduce two mechanisms, one \strict," the other \tolerant," and analyze their a ects on the stability and e ciency of negotiation outcomes.De nition 1 A State Oriented Domain (SOD) is a tuple < S; A; J; c > where:1. S is the set of all possible world states; 2. A = fA 1 ; A 2 ; : : :A n g is an ordered list of agents; 3. J is the set of all possible joint (i.e., n-agent) plans. A joint plan J 2 J moves the world from one state in S to another. The actions taken by agent k are called k's role in J, and will be written as J k . We can also write J as (J 1 ; J 2 ; : : :; J n ); 4. c is a function c: J ! (IR + ) n : For each joint plan J in J , c(J) is a vector of n positive real numbers, the cost of each agent's role in the joint plan. c(J) i is the i-th element of the cost vector, i.e., it is the cost of the i-th role in J. If an agent plays no role in J, his cost is 0.

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Negotiation in a non-cooperative environment

Cited by 27 publications

References 6 publications

Planning to please: Following another agent's intended plan

Planning to please: Following another agent's intended plan

Sensor Web coalition formation via argumentation-based negotiation

Mechanisms for Automated Negotiation in State Oriented Domains

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