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Issues in Automated Negotiation and Electronic Commerce: Extending the Contract Net Framework
, 1999
"... In this paper we discuss a number of previously unaddressed issues that arise in automated negotiation among selfinterested agents whose rationality is bounded by computational complexity. These issues are presented in the context of iterative task allocation negotiations. First, the reasons ..."
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Cited by 244 (24 self)
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In this paper we discuss a number of previously unaddressed issues that arise in automated negotiation among selfinterested agents whose rationality is bounded by computational complexity. These issues are presented in the context of iterative task allocation negotiations. First, the reasons why such agents need to be able to choose the stage and level of commitment dynamically are identified. A protocol that allows such choices through conditional commitment breaking penalties is presented. Next, the implications of bounded rationality are analyzed. Several tradeoffs between allocated computation and negotiation benefits and risk are enumerated, and the necessity of explicit local deliberation control is substantiated. Techniques for linking negotiation items and multiagent contracts are presented as methods for escaping local optima in the task allocation process. Implementing both methods among selfinterested bounded rational agents is discussed. Finally, the ...
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 202 (26 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
Negotiation Among Selfinterested Computationally Limited Agents
, 1996
"... A Dissertation Presented by TUOMAS W. SANDHOLM ..."
Contract types for satisficing task allocation: I Theoretical results
 IN PROC. AAAI SPRING SYMPOSIUM: SATISFICING MODELS
, 1998
"... We analyze task reallocation where individually rational (IR) agents (re)contract tasks among themselves based on marginal costs. A task allocation graph is introduced as a tool for analyzing contract types. Traditional single task contracts always have a short path (sequence of contracts) to the op ..."
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Cited by 103 (8 self)
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We analyze task reallocation where individually rational (IR) agents (re)contract tasks among themselves based on marginal costs. A task allocation graph is introduced as a tool for analyzing contract types. Traditional single task contracts always have a short path (sequence of contracts) to the optimal task allocation but an IR path may not exist, or it may not be short. We analyze an algorithm for finding the shortest IR path. Next we introduce cluster contracts, swaps, and multiagent contracts. Each of the four contract types avoids some local optima that the others do not. Even if the protocol is equipped with all four types, local optima exist. To attack this problem, we introduce OCSMcontracts which combine the ideas behind the four earlier types into an atomic contract type. If the protocol is equipped with OCSMcontracts, any sequence of IR contracts leads to the optimal task allocation in a finite number of steps: an oracleor speculationis not needed for choosing the pa...
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 85 (14 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.
Ruffled by ridges: How evolutionary algorithms can fail
 Genetic and Evolutionary Computation — GECCO 2004
, 2004
"... Abstract. The representations currently used by local search and some evoluationary algorithms have the disadvantage that these algorithms are partially blind to “ridges ” in the search space. Both heuristics search and gradient search algorithms can exhibit extremely slow convergence on functions t ..."
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Cited by 13 (3 self)
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Abstract. The representations currently used by local search and some evoluationary algorithms have the disadvantage that these algorithms are partially blind to “ridges ” in the search space. Both heuristics search and gradient search algorithms can exhibit extremely slow convergence on functions that display ridge structures. A class of rotated representations are proposed; these rotated representations can be based on Principal Components Analysis, or use the GramSchmidt orthogonalization method. Preliminary experiments show that local search using a rotated representation is able to align the coordinates of the search with ridge structures. Search using a rotated representation can convergence are as much as 1000 times faster than local search using a fixed coordinate representation. 1
Examining The Role Of Local Optima And Schema Processing In Genetic Search
, 1999
"... Several factors contribute to making search problems easy or difficult. One of these factors is the modality of the fitness landscape. Quite often, when local search algorithms fail to locate the global optimum, it is because the algorithm converged to a local optimum. The majority of local search ..."
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Cited by 12 (0 self)
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Several factors contribute to making search problems easy or difficult. One of these factors is the modality of the fitness landscape. Quite often, when local search algorithms fail to locate the global optimum, it is because the algorithm converged to a local optimum. The majority of local search methods in use today maneuver through the search space using local neighborhood information around a single point to guide the search. In that search paradigm, the number of local optima that occur in the search space has a tremendous effect on search performance. Genetic
Automatically Constructing Compiler Optimization Heuristics Using Supervised Learning
, 2004
"... This dissertation is dedicated to my mom, Maria, whose love and support made it possible. ACKNOWLEDGMENTS Eliot Moss has been a great thesis advisor. He has helped me to become a better researcher by shaping my critical thinking as well as by improving my expressive skills. I would like to thank th ..."
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Cited by 4 (1 self)
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This dissertation is dedicated to my mom, Maria, whose love and support made it possible. ACKNOWLEDGMENTS Eliot Moss has been a great thesis advisor. He has helped me to become a better researcher by shaping my critical thinking as well as by improving my expressive skills. I would like to thank the members of my thesis committee, Andy Barto, Emery Berger, and Wayne Burleson for their feedback and advice that helped to improve the overall quality of this dissertation. I gratefully acknowledge the friendships and interactions from all members of the Architecture and Language Implementation group (ALI). Beginning with my first lab meeting talk, I have received helpful feedback on the best way to present myself and my work. The ongoing discussions in the lab helped to stimulate my research. Thanks especially to M. Tyler Maxwell for some of the amazing diagrams in this dissertation. Robbie Moll was helpful at stimulating my research interests in the applications of machine learning and for believing in me as an instructor. I especially would like to acknowledge Emmanuel Agu, who has been a good friend and with whom I have had many rewarding discussions on research and life. Finally, I am extremely grateful for the love and support of my entire family. Overall, I am extremely lucky to be part of such a close and wonderful family. I would like to express my sincerest gratitude to my mother, Maria. As a young child I remember my mother always telling me that I could accomplish anything that I set my mind to. She was right as always. Her confidence in me gave me the strength both to overcome any difficulties and to maintain high goals. This work was supported by National Physical Science Consortium and Lawrence Livermore National Laboratory.
Development of problemspecific Evolutionary Algorithms
, 1998
"... . It is a broadly accepted fact that evolutionary algorithms (EA) have to be developed problemspecifically. Usually this is based on experience and experiments. Though, most EA environments are not suited for such an approach. Therefore, this paper proposes a few basic concepts which should be ..."
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Cited by 3 (0 self)
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. It is a broadly accepted fact that evolutionary algorithms (EA) have to be developed problemspecifically. Usually this is based on experience and experiments. Though, most EA environments are not suited for such an approach. Therefore, this paper proposes a few basic concepts which should be supplied by modern EA simulators in order to serve as a toolkit for the development of such algorithms. 1 Introduction Theoretical work as well as practical experience demonstrate the importance to progress from fixed, rigid schemes of evolutionary algorithms (EA) towards a problemspecific processing of optimization problems. Since the "No Free Lunch" theorem [WM97] proves that there is no algorithm which performs better than any other algorithm for all kinds of possible problems, it is useless to judge an algorithm irrespectively of the optimization problem. Therefore, it is necessary to find a suitable algorithm for each problem. Experience has shown that the adaptation of a problem ...
The Dynamics of Evolution Strategies in the Optimization of Traveling Salesman Problems
 IN PROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE, EVOLUTIONARY PROGRAMMING
, 1997
"... An analysis of the dynamic behavior of Evolution Strategies applied to Traveling Salesman Problems is presented. For a special class of Traveling Salesman Problems a stochastic model of the optimization process is introduced. Based on this model different features determining the optimization proces ..."
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Cited by 1 (0 self)
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An analysis of the dynamic behavior of Evolution Strategies applied to Traveling Salesman Problems is presented. For a special class of Traveling Salesman Problems a stochastic model of the optimization process is introduced. Based on this model different features determining the optimization process of Evolution Strategies are analyzed. In addition the stochastic model is extended to explain some aspects of Simulated Annealing.