288 research outputs found

    Mechanisms for Automated Negotiation in State Oriented Domains

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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 define State Oriented Domains, a general category of interaction. Necessary and sufficient conditions for cooperation are outlined. We use the notion of worth in an altered definition of utility, thus enabling agreements in a wider class of joint-goal reachable situations. An approach is offered for conflict resolution, and it is shown that even in a conflict situation, partial cooperative steps can be taken by interacting agents (that is, agents in fundamental conflict might still agree to cooperate up to a certain point). A Unified 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 stand-alone 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 affects on the stability and efficiency of negotiation outcomes.Comment: See http://www.jair.org/ for any accompanying file

    Power and welfare in bargaining for coalition structure formation

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    We investigate a noncooperative bargaining game for partitioning n agents into non-overlapping coalitions. The game has n time periods during which the players are called according to an exogenous agenda to propose offers. With probability δ, the game ends during any time period t< n. If it does, the first t players on the agenda get a chance to propose but the others do not. Thus, δ is a measure of the degree of democracy within the game (ranging from democracy for δ= 0 , through increasing levels of authoritarianism as δ approaches 1, to dictatorship for δ= 1). We determine the subgame perfect equilibrium (SPE) and study how a player’s position on the agenda affects his bargaining power. We analyze the relation between the distribution of power of individual players, the level of democracy, and the welfare efficiency of the game. We find that purely democratic games are welfare inefficient and that introducing a degree of authoritarianism into the game makes the distribution of power more equitable and also maximizes welfare. These results remain invariant under two types of player preferences: one where each player’s preference is a total order on the space of possible coalition structures and the other where each player either likes or dislikes a coalition structure. Finally, we show that the SPE partition may or may not be core stable

    Multi-Agent Systems

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    A multi-agent system (MAS) is a system composed of multiple interacting intelligent agents. Multi-agent systems can be used to solve problems which are difficult or impossible for an individual agent or monolithic system to solve. Agent systems are open and extensible systems that allow for the deployment of autonomous and proactive software components. Multi-agent systems have been brought up and used in several application domains

    Metaphor-based negotiation and its application in AGV movement planning

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    The theme of this thesis is "metaphor-based negotiation". By metaphor-based negotiation I mean a category of approaches for problem-solving in Distributed Artificial Intelligence (DAI) that mimic some aspects of human negotiation behaviour. The research in this dissertation is divided into two closely related parts. Cooperative interaction among agents in a multiagent system (MAS) is discussed in general, and the discussion leads to a formal definition of metaphor-based negotiation. Then, as a specific application, a "spring-based" computational model for metaphor-based negotiation is developed as an approach to solving movement planning, specifically the AGV scheduling problem (AGVSP) — determing the timings of AGVs' activities, of automated guided vehicles (AGVs) in a factory.By formally addressing the multi-agent cooperative interaction problem and assuming that agents in a MAS are rational, benevolent and fully informed, an initial strategy set of cooperative interaction can be reduced to a strategy set by eliminating strategies that are irrational in a group sense. However, it is proved in this dissertation that, in the remaining strategy set, no unique strategy can be found that is acceptable to all agents according their individual preferences. More specifically, in this smaller strategy set, if one agent moves from one strategy to another in an attempt to better its individual goal achievement, then there is at least one agent whose goal achievement will be negatively affected by such a move. So, the cooperative interaction problem can only be partially solved if no further knowledge is given to those agents. The idea of a common sense principle is introduced in this dissertation to overcome the deficiencies of the assumptions of rationality, benevolence and full-informedness.In reality, the assumption of full-informedness of agents may not be practical. Communication is needed for agents to (1) exchange their local problem solving information, and (2) exchange proposals for global problem solving, when their views are in conflict. Based on the discussion of cooperative interaction, a formal definition of metaphorbased negotiation is proposed to formally indicate what is a proposal and what is the condition for accepting a proposal from another agent. In this definition, the common sense principle is one of the most important features, not found in definitions of negotiation available so far in the literature, which guides agents to find an agreement when negotiation is running into difficulties.The AGVSP involves timing activities for each AGV in a AGV-based factory. The AGVSP is naturally distributed: the whole problem can be easily divided into several subproblems each of which involves timing of activities of one AGV. Therefore, it is intuitively straightforward for us to seek DAI approaches to solving the AGVSP. In spired by Kwa's Iterative Negotiation Model [Kwa 88b] [Kwa 88a] for the AGVSP, we developed a spring-based (metaphor-based) negotiation model for the AGVSP to overcome some vital problems in Kwa's model. The idea of the spring-based negotiation model is described below:The AGVSP can be regarded as a Distributed Constraint Satisfaction Problem (DCSP) and solved in a MAS. Each agent in the MAS is designed to solve a subproblem — a local scheduling problem which is a small Constraint Satisfaction Problem (CSP). Conflicts exist when intra-agent constraints or inter-agent constraints are violated. These constraints can be classified into hard constraints— those that can not be relaxed at the agent level unless the system designer permits (e.g., by providing an arbitrator), and soft constraints — those that can be relaxed at the agent level when necessary. When agents are in conflict, i.e, when some inter-agent constraints are violated (or say, when one agent's timings of its activities overlap those of some other agents), these agents involved will resolve the conflicts through a (metaphor-based) negotiation procedure in which conflicts will be gradually resolved by each agent's relaxation of its intra-agent constraints, i.e, by yielding some amount of its initially allocated resources to other agents or by shifting its initially allocated resources. The negotiation can be viewed as a process of exchanging proposals (of cooperative strategies) between conflicting agents, where a cooperative strategy is a possible resolution to a conflict according to the viewpoint of the proposing agent. However, since agents are designed to be rational, each agent that is involved in the conflicts will try hard to relax its intra-agent constraints as little as possible. Further, it is reasonably acceptable that the more an intra-agent constraint has been relaxed the less the respective agent is willing to relax it further. This feature can be modeled by a spring — the more it has been compressed the harder it is to compress it further. Based on this inspiration, a spring-based computational model of metaphor-based negotiation is proposed: each agent's local schedule is represented by a local spring network in which each spring element represents a soft intra-agent constraint. Relaxation of an intra-agent constraint is likened to a spring being compressed by external forces from other agents. As a consequence, the compressed spring will also show a reacting force upon those compressing agents. An agreement will be reached when those forces and reacting forces are balanced. This is the common sense principle in the spring-based negotiation. The model solves some key issues, e.g., how to select negotiation techniques and skills during the process of negotiation, that have not been solved by Kwa's iterative negotiation model. Some experimental evidence of the value of this model is presented

    Endogenous coalition formation and bargaining

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    Multi-agent Collision Avoidance Using Interval Analysis and Symbolic Modelling with its Application to the Novel Polycopter

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    Coordination is fundamental component of autonomy when a system is defined by multiple mobile agents. For unmanned aerial systems (UAS), challenges originate from their low-level systems, such as their flight dynamics, which are often complex. The thesis begins by examining these low-level dynamics in an analysis of several well known UAS using a novel symbolic component-based framework. It is shown how this approach is used effectively to define key model and performance properties necessary of UAS trajectory control. This is demonstrated initially under the context of linear quadratic regulation (LQR) and model predictive control (MPC) of a quadcopter. The symbolic framework is later extended in the proposal of a novel UAS platform, referred to as the ``Polycopter" for its morphing nature. This dual-tilt axis system has unique authority over is thrust vector, in addition to an ability to actively augment its stability and aerodynamic characteristics. This presents several opportunities in exploitative control design. With an approach to low-level UAS modelling and control proposed, the focus of the thesis shifts to investigate the challenges associated with local trajectory generation for the purpose of multi-agent collision avoidance. This begins with a novel survey of the state-of-the-art geometric approaches with respect to performance, scalability and tolerance to uncertainty. From this survey, the interval avoidance (IA) method is proposed, to incorporate trajectory uncertainty in the geometric derivation of escape trajectories. The method is shown to be more effective in ensuring safe separation in several of the presented conditions, however performance is shown to deteriorate in denser conflicts. Finally, it is shown how by re-framing the IA problem, three dimensional (3D) collision avoidance is achieved. The novel 3D IA method is shown to out perform the original method in three conflict cases by maintaining separation under the effects of uncertainty and in scenarios with multiple obstacles. The performance, scalability and uncertainty tolerance of each presented method is then examined in a set of scenarios resembling typical coordinated UAS operations in an exhaustive Monte-Carlo analysis
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