Y. Shoham and M. Tennenholtz. On the Synthesis of Useful Social Laws for Artificial Agent Societies. In Proceedings of the Tenth National Conference on Artificial Intelligence (AAAI-92), San Diego, USA, 1992.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....The agent cannot change its behavior over time, based on experience. On the other hand, there are more complex normative agents for multi agents systems, mainly with the purpose of reducing or transaction costs but in these agents norms are simply built in constraints in the agent s architecture [18, 19] or rules and protocols the agent necessarily applies [14] Boman [1] introduces norms in his agent architecture to overcome serious limitations of rational decisionmaking. However, in this architecture norms act only from outside the decision maker: they don t generate goals or meta criteria to ....

Shoham, Y and Tenneholtz, M. (1992a). On the synthesis of useful social laws for artificial agent societies (preliminary report). Proceedings of the AAAI Conference, 276-281.

....has as one of its main characteristics a low rate of adaptability (see [29] for a discussion on the impossibility of an optimal organizational structure) When flexibility is of essence, other solutions are called for. An intermediate solution is internalized control, e.g. the use of social laws [102]. The most flexible system involves a set of norms and learning at all levels, including the level of norms, based on reflecting upon the results of actions. Structural coordination as proposed in [90] is another example of an intermediate solution that is only suitable for closed systems (or at ....

....I will leave it to the reader to depict these upon the reasons for obeying as developed by Tuomela and described in the previous subsection. 2.3.3 Multiagent Systems Research and Norms The use of norms in artificial agents is a fairly recent development in multiagent systems research (c.f. e.g. [102], 124] 12] Even within multiagent systems research di#erent definitions of norms are used. In [39] pp. 91 92) the following views on norms in multiagent system research are described: norms as constraints on behavior . norms as ends (or goals) norms as obligations Most research on ....

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Y. Shoham and M. Tennenholtz. On the Synthesis of Useful Social Laws for Artificial Agent Societies (Preliminary Report). In Proceedings of the National Conference on Artificial Intelligence, pages 276--281, San Jose, CA, July 1992.

....agents perform based on information about the state of the environment, as well as the use of learning to allow agents to improve their decision making over time. The social commitment policies that we have defined in our work differ from the social laws used in other multi agent planning work [38]. Social laws provide constraints on agents that allow their actions to be coordinated; these laws constrain the ways agents do actions so that their activities do not negatively interact. In contrast, social commitment policies concern rational choice and the ways in which a society can influence ....

Shoham, Y. and Tennenholtz, M. 1992. On the synthesis of useful social laws for artificial agent societies. In: Proc. of AAAI-92, pp. 276-281.

....called a robot, sometimes an agent, and sometimes a particle. The rules are sometimes called social laws, and sometimes called basic behaviors. Moses and Tennenholtz [22,23] investigated several basic principles and formal aspects of distributed con trol with social laws. Shoham and Tennenholtz [33] studied the complexity of automatically deriving useful social laws to achieve certain goals. Parker [24] studied the problem of balancing global knowledge and local knowledge in designing cooperative robotic systems. He regards the information derivable from a robot s sensory and reflecting the ....

Y. Shoham, M. Tennenholtz, On the synthesis of useful social laws for artificial agent societies, in: Proceedings Tenth National Conference on Artificial Intelligence (AAAI-92), San Jose, CA, 1992, pp. 276-281.

....change its behaviour over time, based on experience. On the other hand, there are more complex normative agents for multi agent systems, mainly with the purpose of reducing coordination or transaction costs but in these agents norms are simply built in constraints in the agent s architecture [22], 23] or rules and protocols the agent necessarily applies [17] Boman [2] interestingly introduces norms in his agent architecture to overcome serious limitations of rational decision making, for example in order to have a threshold of unacceptable damages, or to take care of the advantages of ....

Shoham, Y and Tenneholtz, M. (1992a). On the synthesis of useful social laws for artificial agent societies (preliminary report). Proceedings of the AAAI Conference, 276281.

....that the community of agents embody these principles because, in computational settings, we expect agent designers will build multiple agents that at different times come together to form teams. Social commitment policies differ from the social laws used in other multi agent planning work (Shoham and Tennenholtz, 1992). Social laws provide constraints on agents that allow their actions to be coordinated; these laws constrain the ways agents do actions so that their activities do not negatively interact. In contrast, social commitment policies concern rational choice and the ways in which a society can influence ....

Shoham, Y. and Tennenholtz, M. 1992. On the synthesis of useful social laws for artificial agent societies. In: Proceedings of AAAI-92, pages 276-281.

....spirit to the social commitment policies that SPIRE incorporates, they are aimed at group formation, not at conflicting intentions. Furthermore, Iannaccone s approach is not applicable to agents that face multiple decision points over time. The social commitment policies in SPIRE also differ from Shoham and Tennenholtz s (1992) social laws. Social laws constrain the ways agents do actions whereas social commitment policies constrain decision making. Social laws are by their nature domain specific; they constrain domain actions. In contrast, social commitment policies affect decision making across domains and tasks. The ....

Shoham, Y. and Tennenholtz, M. 1992. On the synthesis of useful social laws for artificial agent societies. In: Proceedings of AAAI-92, pages 276-281.

.... with other intelligent agents Therefore, areas of interest in MAS research include game theoretic analysis of multiagent interactions (cf. 62] 142] 143] reasoning about other agents goals, beliefs, and actions (cf. 141] 64] 65] and analysis of the complexity of social interactions [148]. Work in MAS has tended to be theoretical and in very abstract domains. A common underlying assumption is that although the agents may be selfish, they are rational and highly deliberative. This is in stark contrast with research in swarm intelligence (see Section 2.5) in which individual ....

Y. Shoham and M. Tennenholtz. On the synthesis of useful social laws for artificial agent societies (preliminary report). In Proc. AAAI, pages 276--281,

....level cooperation, agents lose the autonomy, because the society of agents is just like a industry workshop or a management organization. Autonomy is an important characteristic in MAS. There are several notable efforts for describing autonomy, e.g. artificial social systems [ 24 ] social laws [ 33 ] establish cooperation through the formalization of agents intentions [ 12 ] 13 ] reaching consensus by negotiation [ 4 ] 8 ] 17 ] 28 ] 34 ] or by economic decision process [ 10 ] and building ideal rational agents [ 29 ] For this kind of cooperation, the information level ....

Y. Shoham and M. Tennenholtz, On the synthesis of useful social law for artificial agent societies, in: Proceedings of AAAI-92, San Joes, CA, 1992, 276-281.

....refer to all this as to the coordination problem. Investigations into the coordination problem can be divided into three general classes: those based on convention, those based on communication, and those based on learning. Some example in the first class was given in AI by Shoham and Tennenholtz [25, 24], where some social laws or conventions [11] are imposed by the system designer (see also [20] so that optimal joint action is assured. In the second class, agents coordination is based on communication (see for instance [28] This second class might be thought as a special case of the ....

Y. Shoham and M. Tennenholtz. On the synthesis of useful social laws for artificial agent societiesp. In Proceedings of the Tenth National Conference on Artificial Intelligence, pages 276--281, San Jose, 1992.

....method of coordinating. Given this fact, we believe agents should be free to adopt, at run time, the method that they believe is best suited to their current situation. Thus, for example, in relatively stable environments social laws may be adopted as the most appropriate means of coordinating [10], whereas in highly dynamic situations one o# contracting models may be better suited [11] and in between, mechanisms that involve the high level interchange of participants goals may be best [4] To achieve this degree of flexibility, agents need to be equipped with a suite of coordination ....

....the relative value of using di#erent CMs is indeed a#ected by the both the individual characteristics of an agent and its beliefs about the environment in which it operates. 6 Related Work The majority of previous work on multi agent system coordination assumes it is a design time problem (e.g. [10, 11, 4]) However [5] has argued that agents need the flexibility to coordinate at di#erent levels of abstraction, depending upon their particular needs at a given moment in time. To date, however, this work has not developed mechanisms for explicitly reasoning about which level to coordinate at in a ....

Y. Shoham and M. Tennenholtz. On the synthesis of useful social laws for artificial agent societies. In Proc. of the 10th Nat. Conf. on AI, San Diego, CA, 1992.

....unit or as a pluralistic and decentralised set of interrelated units. Moreover, MAS theory and practice offer a rich set of tools and mechanisms for explicitly representing a number of organisational structures and phenomena (e.g. roles (Barbuceanu 1997) plans (Kinny et al. 1992) norms (Shoham and Tennenholtz 1992)) Given this, we now need to evaluate whether and to what extent this organisational design perspective of the agent based approach can offer an adequate means for modelling our domain, and in particular its structural and organisational variables and properties. Going public is a complex process ....

Shoham, Y., and M. Tennenholz. (1992). "On the Synthesis of Useful Social Laws For Artificial Agent Societies", in Proceedings of the Tenth National Conference on Artificial Intelligence, AAAI-92, San Jose, CA, pp. 276-280.

....effective social relationships in certain situations 1 . We have been interested in agent strategies for interactions with other agents that can promote cooperation in groups. Our approach is different from other researchers who have designed effective social laws that can be imposed on agents [17]. In particular, we have studied environments where agents can mutually benefit from sustained interactions. The goal of our work is to develop strategies that promote cooperation among homogeneous groups and can resist exploitation by malevolent agents in such environments. Such strategies can ....

Y. Shoham and M. Tennenholtz. On the synthesis of useful social laws for artificial agent societies (preliminary report). In Proceedings of the National Conference on Artificial Intelligence, pages 276--281, San Jose, California, July 1992.

....a straightforward way of achieving coordination in a multi robot system. In general, designing all necessary conventions is difficult and perhaps intractable (Shoham Tennenholtz 1995) but it has been shown that conventions can be reached without centralized control if agents interact and learn (Shoham Tennenholtz 1992). Shoham proposes a set of social laws for a group of idealized mobile robots that allow them to move on a grid without colliding and interfering. The social laws are basically traffic laws that control how the robots move, what they should do when they get to junctions, etc. The assumption is ....

Shoham, Y., and Tennenholtz, M. 1992. On the synthesis of useful social laws for artificial agent societies (preliminary report). In Proc. Nat'l Conf. on Artificial Intelligence, 276--281.

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Y. Shoham and M. Tennenholtz. On the Synthesis of Useful Social Laws for Artificial Agent Societies. In Proceedings of the Tenth National Conference on Artificial Intelligence (AAAI-92), San Diego, USA, 1992.

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Shoham Y., Tennenholtz M. (1992) On the Synthesis of Useful Social Laws for Artificial Agent Societies. Proceedings of AAAI-92

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Y. Shoham and M. Tennenholtz. On the synthesis of useful social laws for artificial agent societies. In Proceedings of the Tenth National Conference on Artificial Intelligence (AAAI-92), San Diego, CA, 1992.

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Y. Shoham and M. Tennenholtz. On the synthesis of useful social laws for artificial agent societies. In Proc. AAAI-92, 1992.

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Y. Shoham and M. Tennenholtz. On the synthesis of useful social laws for artificial agent societies. In Proc. of AAAI 92, pages 276--281, 1992.

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Shoham, Y., Tennenholtz, M.: On the synthesis of useful social laws for artificial agent societies. In: Proceedings of the 10th National Conference on Artificial Intelligence (AAAI92) , San Diego, CA. (1992) 276--281

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Y. Shoham and M. Tennenholtz, "On the synthesis of useful social laws for artificial agent societies," in Proceedings of the Tenth National Conference on Artificial Intelligence (AAAI-92). San Jose, California, 1992, pp. 276--281.

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Y. Shoham and M. Tennenholtz. On the synthesis of useful social laws for artificial agent societies. In Proceedings of the Tenth National Conference on Artificial Intelligence (AAAI92) , pages 276--281, San Jose, California, July 1992.

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Y. Shoham and M. Tennenholtz. On the Synthesis of Useful Social Laws for Artificial Agent Societies. In Proc. of 10th National Conf. on AI, San Jose, USA, 1992.

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Shoham, Y. and Tennenholtz, M. 1992. On the synthesis of useful social laws for artificial agent societies. In: Proc. of AAAI-92, pp. 276-281.

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Yoav Shoham and Moshe Tennenholtz. On the synthesis of useful social laws for artificial agent societies (preliminary report). In Proceedings of the National Conference on Artificial Intelligence, San Jose, California, July 1992.

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