A5087505541- Multi-Agent Systems and Negotiation
- Distributed Control Multi-Agent Systems
- Reinforcement Learning in Robotics
- AI-based Problem Solving and Planning
- Human-Automation Interaction and Safety
- Logic, Reasoning, and Knowledge
- Auction Theory and Applications
- Semantic Web and Ontologies
- Modular Robots and Swarm Intelligence
- Optimization and Search Problems
- Robotic Path Planning Algorithms
- Mobile Agent-Based Network Management
- Constraint Satisfaction and Optimization
- Team Dynamics and Performance
- Game Theory and Applications
- Adversarial Robustness in Machine Learning
- Opinion Dynamics and Social Influence
- Cognitive Science and Mapping
- Topic Modeling
- Domain Adaptation and Few-Shot Learning
- Evolutionary Game Theory and Cooperation
- Complex Network Analysis Techniques
- Service-Oriented Architecture and Web Services
- Business Process Modeling and Analysis
- Explainable Artificial Intelligence (XAI)
Carnegie Mellon University
2015-2024
Raghudeep Eye Hospital
2018
Clarkson University
2018
University of Pittsburgh
2002-2015
United States Army Research Office
2014
University of Southern California
2014
University of Aberdeen
2009-2011
Polytechnic University of Turin
2000
Panasonic (Japan)
1994
Osaka University
1994
In Retsina, the authors have developed a distributed collection of software agents that cooperate asynchronously to perform goal-directed information retrieval and integration for supporting variety decision-making tasks. Examples everyday organizational decision making financial portfolio management demonstrate its effectiveness.
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Recent advances in technology are delivering robots of reduced size and cost. A natural outgrowth these systems comprised large numbers that collaborate autonomously diverse applications. Research on effective autonomous control such systems, commonly called swarms, has increased dramatically recent years received attention from many domains, as bioinspired robotics theory. These kinds distributed present novel challenges for the integration human supervisors, operators, teammates only...
This work establishes an architecture for Urban Search and Rescue a methodology mixing real-world simulation-based testing. A sensor suite fusion algorithm robust victim detection permits aggregation of readings from various sensors on multiple robots. We have embarked research program focusing the enabling technologies effective USAR robotic rescue devices. The is also researching system-level design, evaluation, refinement architectures that include teams sensor-laden robots human...
In peer-to-peer (P2P) systems, peers often must interact with unknown or unfamiliar without the benefit of trusted third parties authorities to mediate interactions. A peer needs reputation mechanisms incorporate knowledge others decide whether trust another party in P2P systems. This paper discusses design and proposes a distributed mechanism detect malicious unreliable It illustrates process for rating gathering aggregation presents some experimental results evaluate proposed approach....
A model of decentralized problem solving, called distributed constrained heuristic search (DCHS), that provides both structure and focus in individual agent spaces to optimize decisions the global space, is presented. The achieves this by integrating constraint satisfaction search. It a formalism suitable for describing large set artificial intelligence problems. notion textures allow agents operate an asynchronous concurrent manner introduced. use coupled with backjumping, type...
In open, dynamic multi-agent systems, agents may form short-term ad-hoc groups, such as coalitions, in order to meet their goals. Trust and reputation are crucial concepts these environments, must rely on peers perform expected, learn avoid untrustworthy partners. However, groups introduce issues which impede the formation of trust relationships. For example, they be short-lived, precluding from gaining necessary experiences make an accurate evaluation. This paper describes a new approach,...
Autonomous AI systems will be entering human society in the near future to provide services and work alongside humans. For those accepted trusted, users should able understand reasoning process of system, i.e. system transparent. System transparency enables humans form coherent explanations system's decisions actions. Transparency is important not only for user trust, but also software debugging certification. In recent years, Deep Neural Networks have made great advances multiple...
We present distributed algorithms for multirobot task assignment where the tasks have to be completed within given deadlines. Each robot has a limited battery life and thus there is an upper limit on amount of time that it perform tasks. Performing each requires certain (called duration) can different payoffs Our problem assign robots such total payoff maximized while respecting deadline constraints robot's constraints. NP-hard since special case our classical generalized (which NP-hard)....
Buyer coalitions are beneficial in e-marketplaces because they allow buyers to take advantage of volume discounts. However, existing buyer coalition formation schemes do not provide with any means declare and match their preferences or calculate the division surplus a stable manner. Concepts algorithms for have been investigated game theory multi-agent systems research, but computational complexity, cannot deal thousands which could join practice. In this paper, we propose new scheme...
We are investigating techniques for developing distributed and adaptive collections of information agents that coordinate to retrieve, filter fuse relevant the user, task situation, as well anticipate user's needs. In our system agents, gathering is seamlessly integrated with decision support. The which particular requested does not remain in head but it explicitly represented supported through agent collaboration. this paper we present architecture, collaboration interactions, a reusable...
Today's service-oriented systems realize many ideas from the research conducted a decade or so ago in multiagent systems. Because these two fields are deeply connected, further advances could feed into tomorrow's successful computing approaches. This article describes 15-year roadmap for system research.