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  • 1
    Electronic Resource
    Electronic Resource
    Model Selection in an Information Economy: Choosing What to Learn (2002)
    Boston, USA and Oxford, UK : Blackwell Publishers Inc.
    Computational intelligence 18 (2002), S. 0 
    Details
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: As online markets for the exchange of goods and services become more common, the study of markets composed, at least in part, of autonomous agents has taken on increasing importance. In contrast to traditional complete–information economic scenarios, agents that are operating in an electronic marketplace often do so under considerable uncertainty. In order to reduce their uncertainty, these agents must learn about the world around them. When an agent producer is engaged in a learning task in which data collection is costly, such as learning the preferences of a consumer population, it is faced with a classic decision problem: when to explore and when to exploit. If the agent has a limited number of chances to experiment, it must explicitly consider the cost of learning (in terms of foregone profit) against the value of the information acquired. Information goods add an additional dimension to this problem; due to their flexibility, they can be bundled and priced according to a number of different price schedules. An optimizing producer should consider the profit each price schedule can extract, as well as the difficulty of learning of this schedule.In this paper, we demonstrate the tradeoff between complexity and profitability for a number of common price schedules. We begin with a one–shot decision as to which schedule to learn. Schedules with moderate complexity are preferred in the short and medium term, as they are learned quickly, yet extract a significant fraction of the available profit. We then turn to the repeated version of this one–shot decision and show that moderate complexity schedules, in particular two–part tariff, perform well when the producer must adapt to nonstationarity in the consumer population. When a producer can dynamically change schedules as it learns, it can use an explicit decision–theoretic formulation to greedily select the schedule which appears to yield the greatest profit in the next period. By explicitly considering both the learnability and the profit extracted by different price schedules, a producer can extract more profit as it learns than if it naively chose models that are accurate once learned.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1467-8640.t01-2-00204
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  • 2
    Electronic Resource
    Electronic Resource
    Rational Coordination in Multi-Agent Environments (2000)
    Springer
    Autonomous agents and multi-agent systems 3 (2000), S. 319-350 
    Details
    ISSN: 1573-7454
    Keywords: coordination ; rationality ; decision theory ; game theory ; agent modeling
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract We adopt the decision-theoretic principle of expected utility maximization as a paradigm for designing autonomous rational agents, and present a framework that uses this paradigm to determine the choice of coordinated action. We endow an agent with a specialized representation that captures the agent's knowledge about the environment and about the other agents, including its knowledge about their states of knowledge, which can include what they know about the other agents, and so on. This reciprocity leads to a recursive nesting of models. Our framework puts forth a representation for the recursive models and, under the assumption that the nesting of models is finite, uses dynamic programming to solve this representation for the agent's rational choice of action. Using a decision-theoretic approach, our work addresses concerns of agent decision-making about coordinated action in unpredictable situations, without imposing upon agents pre-designed prescriptions, or protocols, about standard rules of interaction. We implemented our method in a number of domains and we show results of coordination among our automated agents, among human-controlled agents, and among our agents coordinating with human-controlled agents.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1010028119149
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  • 3
    Electronic Resource
    Electronic Resource
    Emergent Properties of a Market-based Digital Library with Strategic Agents (2000)
    Springer
    Autonomous agents and multi-agent systems 3 (2000), S. 33-51 
    Details
    ISSN: 1573-7454
    Keywords: multi-agent systems ; digital libraries ; strategic reasoning ; emergent behavior
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract The University of Michigan Digital Library (UMDL) is designed as an open system that allows third parties to build and integrate their own profit-seeking agents into the marketplace of information goods and services. The profit-seeking behavior of agents, however, risks inefficient allocation of goods and services, as agents take strategic stances that might backfire. While it would be good if we could impose mechanisms to remove incentives for strategic reasoning, this is not possible in the UMDL. Therefore, our approach has instead been to study whether encouraging the other extreme—making strategic reasoning ubiquitous—provides an answer. Toward this end, we have designed a strategy (called the p-strategy) that uses a stochastic model of the market to find the best offer price. We have then examined the collective behavior of p-strategy agents in the UMDL auction. Our experiments show that strategic thinking is not always beneficial and that the advantage of being strategic decreases with the arrival of equally strategic agents. Furthermore, a simpler strategy can be as effective when enough other agents use the p-strategy. Consequently, we expect the UMDL is likely to evolve to a point where some agents use simpler strategies and some use the p-strategy.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1010081711284
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  • 4
    Electronic Resource
    Electronic Resource
    A Formal Study of Distributed Meeting Scheduling (1998)
    Springer
    Group decision and negotiation 7 (1998), S. 265-289 
    Details
    ISSN: 1572-9907
    Keywords: meeting scheduling ; intelligent agents ; distributed AI ; probabilistic model ; discrete event simulation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Psychology
    Notes: Abstract Automating routine organizational tasks, such as meeting scheduling, requires a careful balance between the individual (respecting his or her privacy and personal preferences) and the organization (making efficient use of time and other resources). We argue that meeting scheduling is an inherently distributed process, and that negotiating over meetings can be viewed as a distributed search process. Keeping the process tractable requires introducing heuristics to guide distributed schedulers' decisions about what information to exchange and whether or not to propose the same tentative time for several meetings. While we have intuitions about how such heuristics could affect scheduling performance and efficiency, verifying these intuitions requires a more formal model of the meeting schedule problem and process. We present our preliminary work toward this goal, as well as experimental results that validate some of the predictions of our formal model. We also investigate scheduling in overconstrained situations, namely, scheduling of high priority meetings at short notice, which requires cancellation and rescheduling of previously scheduled meetings. Our model provides a springboard into deeper investigations of important issues in distributed artificial intelligence as well, and we outline our ongoing work in this direction.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008639617029
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  • 5
    Electronic Resource
    Electronic Resource
    Toward a theory of honesty and trust among communicating autonomous agents (1993)
    Springer
    Group decision and negotiation 2 (1993), S. 237-258 
    Details
    ISSN: 1572-9907
    Keywords: distributed artificial intelligence ; rational communication ; multiagent systems ; decision making ; agent modeling ; belief
    Source: Springer Online Journal Archives 1860-2000
    Topics: Psychology
    Notes: Abstract This article outlines, through a number of examples, a method that can be used by autonomous agents to decide among potential messages to send to other agents, without having to assume that a message must be truthful and that it must be believed by the hearer. The main idea is that communicative behavior of autonomous agents is guided by the principle of economic rationality, whereby agents transmit messages to increase the effectiveness of interaction measured by their expected utilities. We are using a recursive, decision-theoretic formalism that allows agents to model each other and to infer the impact of a message on its recipient. The recursion can be continued into deeper levels, and agents can model the recipient modeling the sender in an effort to assess the truthfulness of the received message. We show how our method often allows the agents to decide to communicate in spite of the possibility that the messages will not be believed. In certain situations, on the other hand, our method shows that the possibility of the hearer not believing what it hears makes communication useless. Our method thus provides the rudiments of a theory of how honesty and trust could emerge through rational, selfish behavior.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01384248
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  • 6
    Electronic Resource
    Electronic Resource
    Search reduction in hierarchical distributed problem solving (1993)
    Springer
    Group decision and negotiation 2 (1993), S. 301-317 
    Details
    ISSN: 1572-9907
    Keywords: abstraction ; coordination ; distributed artificial intelligence ; multiagent systems ; planning ; search
    Source: Springer Online Journal Archives 1860-2000
    Topics: Psychology
    Notes: Abstract Knoblock and Korf have determined that abstraction can reduce search at a single agent from exponential to linear complexity (Knoblock 1991; Korf 1987). We extend their results by showing how concurrent problem solving among multiple agents using abstraction can further reduce search to logarithmic complexity. We empirically validate our formal analysis by showing that it correctly predicts performance for the Towers of Hanoi problem (which meets all of the assumptions of the analysis). Furthermore, a powerful form of abstraction for large multiagent systems is to group agents into teams, and teams of agents into larger teams, to form an organizational pyramid. We apply our analysis to such an organization of agents and demonstrate the results in a delivery task domain. Our predictions about abstraction's benefits can also be met in this more realistic domain, even though assumptions made in our analysis are violated. Our analytical results thus hold the promise for explaining in general terms many experimental observations made in specific distributed AI systems, and we demonstrate this ability with examples from prior research.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01384251
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  • 7
    Electronic Resource
    Electronic Resource
    A contracting model for flexible distributed scheduling (1996)
    Springer
    Annals of operations research 65 (1996), S. 195-222 
    Details
    ISSN: 1572-9338
    Keywords: Heuristics ; meeting scheduling ; contract net ; search bias ; cancellation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Notes: Abstract We are interested in building systems of autonomous agents that can automate routine information processing activities in human organizations. Computational infrastructures for cooperative work should contain embedded agents for handling many routine tasks [9], but as the number of agents increases and the agents become geographically and/or conceptually dispersed, supervision of the agents will become increasingly problematic. We argue that agents should be provided with deep domain knowledge that allows them to make quantitatively justifiable decisions, rather than shallow models of users to mimic. In this paper, we use the application domain of distributed meeting scheduling to investigate how agents embodying deeper domain knowledge can choose among alternative strategies for searching their calendars in order to create flexible schedules within reasonable cost.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF02187332
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    Paper (German National Licenses)
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  • 8
    Electronic Resource
    Electronic Resource
    Designing tree-structured organizations for computational agents (1996)
    Springer
    Computational & mathematical organization theory 2 (1996), S. 219-245 
    Details
    ISSN: 1572-9346
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract We describe a framework for defining the space of organization designs for computational agents, use our framework for analyzing the expected performance of a class of organizations, and describe how our analyses can be applied to predict performance for a distributed information gathering task. Our analysis specifically addresses the impact of the span of control (branching factor) in tree-structured hierarchical organizations on the response time of such organizations. We show quantitatively how the overall task size and granularity influence the design of the span of control for the organization, and that within the class of organizations considered the apropriate span of control is confined to a relatively narrow range. The performance predicted by our overall model correlates with the actual performance of a distributed organization for computer network monitoring. Consequently, we argue that our framework can support aspects of organizational self-design for computational agents, and might supply insights into the design of human organizations as well.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00127275
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    Paper (German National Licenses)
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  • 9
    Electronic Resource
    Electronic Resource
    Integrated Premission Planning and Execution for Unmanned Ground Vehicles (1998)
    Springer
    Autonomous robots 5 (1998), S. 97-110 
    Details
    ISSN: 1573-7527
    Keywords: cooperating robots ; coordination ; multi-agent system
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract Fielding robots in complex applications can stress the human operators responsible for supervising them, particularly because the operators might understand the applications but not the details of the robots. Our answer to this problem has been to insert agent technology between the operator and the robotic platforms. In this paper, we motivate the challenges in defining, developing, and deploying the agent technology that provides the glue in the application of tasking unmanned ground vehicles in a military setting. We describe how a particular suite of architectural components serves equally well to support the interactions between the operator, planning agents, and robotic agents, and how our approach allows autonomy during planning and execution of a mission to be allocated among the human and artificial agents. Our implementation and demonstrations (in real robots and simulations) of our multi-agent system shows significant promise for the integration of unmanned vehicles in military applications.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008869126852
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    Paper (German National Licenses)
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