Sergey Serebryakov

P2P Agent Platform: Implementation and Testing

Peer-to-Peer (P2P) computing, a novel paradigm for distributed information technology, is currently receiving ever increasing interest from both academia and industry. Recent efforts undertaken to integrate multi-agent and P2P architectures are one of such very promising new opportunities. Indeed, multi-agent system (MAS) may be thought of as a multitude of autonomous entities, and, therefore, structuring the agents as a P2P network of nodes may result in an architecture providing a new dimension for design of open MAS composed of a highly transient population of agents. This paper presents an implementation of a P2P Agent Platform providing transparent interaction for distributed P2P agents. The developed P2P Agent Platform implements the basic mandatory components assumed by the functional architecture proposed by the FIPA Nomadic Agents Working Group. This implementation is supported with a search mechanism, a function of an underlying P2P infrastructure. The platform verification is done via prototyping a P2P ground object detection MAS in which the agents situated on top of the distributed instances of the P2P Agent platform provide classification services.

Multi-agent Peer-to-Peer Intrusion Detection

Ever increasing use of heterogeneous networks including mobile devices and ad-hoc sensor networks signifies the role of such information systems’ properties as openness, autonomy, cooperation, coordination, etc. Agent-based service-oriented Peer-to-Peer (P2P) architecture provides attractive (if not unique) design and implementation paradigm for such systems. This trend implies coherent evolution of security systems, that put in use the notions of distributed security policy, distributed intrusion detection systems, etc.1, requiring novel ideas. The paper proposes new architecture for such security systems. This architecture provides cooperative performance of distributed security means (agents) supported by distributed meta-knowledge base implemented as an overlay network of instances of P2P agent platform set up on top of P2P networking provider. The paper also analyzes new issues of P2P security systems with the main emphasis on P2P training of security agents to correlation of alerts produced by other relevant agents. An artificially built case study is used to highlight the essence of P2P security agent training to P2P decision combining and to exhibit new problems.

Ontology-Based Context-Dependent Personalization Technology

Personalization, a topmost concern of modern recommendation systems (RS), is intended to predict individual motivation of a customer for this or that choice. It depends on many factors forming explicit and implicit decision context. The paper proposes RS personalization technology that focuses on ontology–based extraction of semantically interpretable context of each particular customer’s decisions from his/her historical data sample with the subsequent machine learning–based extraction of customer–centered feature set and personal cause–consequence decision rules. The technology is fully implemented by Practical Reasoning, Inc. and validated via several case studies.

Agent-based distributed decision-making in dynamic operational environments

The paper presents an approach and the supporting software tools for integration of intelligent multi-agent systems and the peer-to-peer (P2P) technologies to support the development of heterogeneous distributed decision making applications operating in dynamic ubiquitous environment. Particularly, the proposed technology integrates two software tools, MASDK 4.0 software tool and a P2P agent platform. MASDK 4.0 is provided with a graphical application specification language that supports the thorough and consistent conceptual analysis, detailed design, code generation and deployment of multi-agent systems applications including those operating in dynamic environments. P2P agent platform is a FIPA compliant middleware enabling transparent P2P interaction of agents operating in heterogeneous and ubiquitous environment. The platform is fully compatible with the multi-agent applications developed by MASDK 4.0. The combined application of MASDK 4.0 and P2P agent platform is demonstrated by a case study of the air traffic control and emergency management. In this case study a model of autonomous air traffic control is implemented by a set of distributed intelligent agents. This application is a typical example of a modem agent-based distributed decision making system operating in a dynamic P2P environment.

Automated P2P Learning in Agent-Based Classification Networks

Peer-to-Peer (P2P) computing is a novel computing paradigm receiving ever increasing attention of the research community. It provides new opportunities in design and implementation of large scale intelligent systems satisfying modern requirements to scalability, autonomy, mobility, fault tolerance, etc. This paradigm becomes particularly attractive if it is integrated with multi-agent systems. The paper is focused on P2P cooperative decision making and P2P machine learning of cooperation of autonomous agents in open P2P networks. It proposes P2P mechanism for decision combining utilized by autonomous decision making agents and for P2P learning of decision combining. The paper results are validated using case study, P2P agent-based intrusion detection system.

P2P Open Agent Networks for Decision Making

Peer-to-peer (P2P) computing, a recently developed network architecture for distributed systems, is currently receiving ever increasing attention of both academia and industry. It has become a driving force for many new ideas and opportunities in design and implementation of modern large scale applications composed of highly autonomous entities. Recent efforts intended to integrate multi-agent, service-orients and P2P architectures aim to make these very promising opportunities happen.