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Negotiation decision functions for autonomous agents
 International Journal of Robotics and Autonomous Systems
, 1998
"... We present a formal model of negotiation between autonomous agents. The purpose of the negotiation is to reach an agreement about the provision of a service by one agent for another. The model de nes a range of strategies and tactics that agents can employ to generate initial o ers, evaluate proposa ..."
Abstract

Cited by 275 (54 self)
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We present a formal model of negotiation between autonomous agents. The purpose of the negotiation is to reach an agreement about the provision of a service by one agent for another. The model de nes a range of strategies and tactics that agents can employ to generate initial o ers, evaluate proposals and o er counter proposals. The model is based on computationally tractable assumptions, demonstrated in the domain of business process management and empirically evaluated. Keywords: Multiagent systems, Negotiation, Business Process Management 1
Coalitions Among Computationally Bounded Agents
 Artificial Intelligence
, 1997
"... This paper analyzes coalitions among selfinterested agents that need to solve combinatorial optimization problems to operate e ciently in the world. By colluding (coordinating their actions by solving a joint optimization problem) the agents can sometimes save costs compared to operating individua ..."
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Cited by 167 (24 self)
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This paper analyzes coalitions among selfinterested agents that need to solve combinatorial optimization problems to operate e ciently in the world. By colluding (coordinating their actions by solving a joint optimization problem) the agents can sometimes save costs compared to operating individually. A model of bounded rationality is adopted where computation resources are costly. It is not worthwhile solving the problems optimally: solution quality is decisiontheoretically traded o against computation cost. A normative, application and protocolindependent theory of coalitions among boundedrational agents is devised. The optimal coalition structure and its stability are signi cantly a ected by the agents ' algorithms ' performance pro les and the cost of computation. This relationship is rst analyzed theoretically. Then a domain classi cation including rational and boundedrational agents is introduced. Experimental results are presented in vehicle routing with real data from ve dispatch centers. This problem is NPcomplete and the instances are so large thatwith current technologyany agent's rationality is bounded by computational complexity. 1
Coalition formation among bounded rational agents
, 1995
"... This paper analyzes coalitions among selfinterested agents that need to solve combinatorial optimization problems to operate efficiently in the world. By colluding (coordinating their actions by solving a joint optimization problem), the agents can sometimes save costs compared to operating individ ..."
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Cited by 74 (12 self)
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This paper analyzes coalitions among selfinterested agents that need to solve combinatorial optimization problems to operate efficiently in the world. By colluding (coordinating their actions by solving a joint optimization problem), the agents can sometimes save costs compared to operating individually. A model of bounded rationality is adopted, where computation resources are costly. It is not worth solving the problems optimally: solution quality is decisiontheoretically traded off against computation cost. A normative, protocolindependent theory of coalitions among bounded rational (BR) agents is devised. The optimal coalition structure and its stability are significantly affected by the agents' algorithms' performance profiles (PPs) and the unit cost of computation. This relationship is first analyzed theoretically. A domain classification including rational and BR agents is introduced. Experimental results are presented in the distributed vehicle routing domain using real data from 5 dispatch centers; the optimal coalition structure for BR agents differs significantly from the one for rational agents. These problems are NPcomplete and the instances are so large that, with current technology, any agent's rationality is bounded by computational complexity.
Agents in electronic commerce: component technologies for automated negotiation and coalition formation
 Autonomous Agents and MultiAgent Systems
"... Abstract. Automated negotiation and coalition formation among selfinterested agents are playing an increasingly important role in electronic commerce. Such agents cannot be coordinated by externally imposing their strategies. Instead the interaction protocols have to be designed so that each agent ..."
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Cited by 39 (1 self)
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Abstract. Automated negotiation and coalition formation among selfinterested agents are playing an increasingly important role in electronic commerce. Such agents cannot be coordinated by externally imposing their strategies. Instead the interaction protocols have to be designed so that each agent is motivated to follow the strategy that the protocol designer wants it to follow. This paper reviews six component technologies that we have developed for making such interactions less manipulable and more efficient in terms of the computational processes and the outcomes: 1. OCSMcontracts in marginal cost based contracting, 2. leveled commitment contracts, 3. anytime coalition structure generation with worst case guarantees, 4. trading off computation cost against optimization quality within each coalition, 5. distributing search among insincere agents, and 6. unenforced contract execution. Each of these technologies represents a different way of battling selfinterest and combinatorial complexity simultaneously. This is a key battle when multiagent systems move into largescale open settings.
Contract Type Sequencing for Reallocative Negotiation
 IN INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS
, 2000
"... The capability to reallocate itemse.g. tasks, securities, bandwidth slices, Mega Watt hours of electricity, and collectiblesis a key feature in automated negotiation. Especially when agents have preferences over combinations of items, this is highly nontrivial. Marginal cost based reallocation ..."
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Cited by 15 (1 self)
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The capability to reallocate itemse.g. tasks, securities, bandwidth slices, Mega Watt hours of electricity, and collectiblesis a key feature in automated negotiation. Especially when agents have preferences over combinations of items, this is highly nontrivial. Marginal cost based reallocation leads to an anytime algorithm where every agent's utility increases monotonically over time. Different contract types head toward different locally optimal task allocations, and contracts from a recently introduced comprehensive contract type, OCSMcontracts, head toward the global optimum. Reaching it can take impractically long, so it is important to trade off solution quality against negotiation time. To construct negotiation protocols that lead to the best achievable allocations in a bounded amount of time, we compared sequences of four contract types: original, cluster, swap, and multiagent contracts. The experiments show that it is profitable to use multiple contract types in the sequ...