Gabriel Jakobson

Situation Management: Basic Concepts and Approaches

This paper scopes the issues of Situation Management in dynamic systems, defines the basic concepts of Situation Management, and identifies several key enabling technologies. Particular focus of the paper is given to situation modeling. The paper reviews major aspects of situation modeling and discusses associated technologies, including Situation Calculus, Situation Semantics, Situation Control, Situation Awareness and others. In more detail we discuss an approach to situation management based on multi-agent systems, event correlation and case-based reasoning.

A Framework of Cognitive Situation Modeling and Recognition

This paper scopes the issues of situation management in dynamic systems, defines the basic concepts, and identifies several key enabling technologies. Particular focus of the paper is given to situation modeling. The paper reviews the major aspects of situation modeling and discusses associated technologies, including situation calculus, situation semantics, situation control, situation awareness and others. In more detail, we present an approach to situation modeling and management which is based on combining multi-agent systems and event correlation

Overview of situation management at SIMA 2005

This paper is an introduction to the Workshop on Situation Management, SIMA 2005. We discuss the scope of the workshop, the big picture of situation management, and a summarization of the papers selected for inclusion in the workshop. Topics include situation knowledge acquisition, learning & situation recognition, structural & behavioral modeling of sensor networks, robotic sensors & mobile sensor grids, advanced architectures for situation awareness, and human-centric situation management. We conclude with a discussion of hard, outstanding challenges in situation management and future R&D areas

Extending BDI Multi-Agent Systems with Situation Management

We extend the BDI (belief desire, intention) agent model by enabling agent beliefs to be based on real-time situations that are generated by a situation management (SM) system. This has several advantages for multi-agent systems using BDI agents. First, because of the use of event correlation and data fusion techniques in situation management, agent platforms can support highly reactive distributed applications. Second, the situation manager provides a semantically rich representation of the world and can dynamically adapt its representation for situations over time. From the system architecture perspective, we discuss several alternatives for how existing BDI-capable agent platforms can incorporate this extension. These alternatives range from complete SM functionality in each agent to having shared SM functionality among multiple agents. We also consider environments where different agent platforms use our situation-based BDI (SBBDI) agent method and must interoperate. We include an example of an SBBDI agent system for homeland security threat assessment

Inferring threats in urban environments with uncertain and approximate data: an agent-based approach

Abstract In this article we discuss the problem of inferring threats in an urban environment, where the knowledge of the environment involves multiple types of intelligence and infrastructure data, and is by nature uncertain or approximate. We use a collection of situation-aware agents to infer potential threats in such environments, where agents are responsible for event correlation and situation assessment. We review the weaknesses of a current approach to threat assessment in Homeland Security and then describe our agent-based approach. The key innovations of our agent-based approach are: an ontological commitment to events and situations, fuzzy event correlation, fuzzy situation assessment, adaptability and learning during threat assessment operations, and an enhancement of traditional belief-desire-intention (BDI) agents with situation awareness. We describe the properties of situation-aware BDI agents and discuss the implementation of them on a variety of BDI agent platforms. Lastly, we discuss the interoperability of these platforms and address the issue of scalability through coupling to large-scale peer-to-peer overlays.

Situation management [Guest editorial]

Many domains, such as physical infrastructure and cyber security monitoring, battlefield operations management, disaster response and crisis management, and homeland security, are characterized by dense realtime sensing, large numbers of distributed heterogeneous information sources, and a variety of distributed, communicating, and network-enabled actors and agents. In these domains there is the need to automatically and continuously identify and act on complex, often incomplete and unpredictable dynamic situations. As a result, effective methods of situation recognition, prediction, reasoning, and control are required - operations collectively identifiable as situation management.

Enabling cyber situation awareness, impact assessment, and situation projection

In the paper we focus on (i) an assessment of impact on missions or business processes resulting from cyber attacks and (ii) the subsequent projection of further possible attacks and corresponding impact assessments. A reference model for impact assessment and situation projection (IASP) is provided, based on which we propose a constraint satisfaction (CS) algorithmic approach for performing IASP. The nodes of a constraint network contain variables with accompanying certainty factors characterizing aspects of missions, services, IT assets, network connections, known vulnerabilities, safeguards, cyber alerts, attack categories, and partial models of complex stepping-stone or island-hopping attacks. Given constraints among these variables, e.g. mission X depends on services Y and Z, the CS algorithm calculates IASP with degree of certainty. We demonstrate the approach on dataset containing audit trails, IDS alerts, and TCP traffic.

Peer-to-peer coupled agent systems for distributed situation management

Large scale situation management applications such as disaster recovery and network-centric battle management are characterized by distributed heterogeneous agent platforms with dynamic agent populations, highly variable network connectivity and bandwidth, and localized situation knowledge and event collection. We describe a new agent model and an integrated peer-to-peer architecture which addresses these requirements. We present an extension of the BDI agent model which allows it to be used in highly reactive applications. We describe the use of multi-hop peer-to-peer overlays which provides highly scalable coupling of distributed agent platforms. Finally, we describe a two-phase semantic discovery mechanism which serves as a basis for agents to share events and situations across the overlay.

Distributed autonomic management: An approach and experiment towards managing service-centric networks

This paper describes a novel approach for managing service-centric communications networks called distributed autonomic management (DAM). Current approaches to network management employ the client/server model, cooperative stationary agents, and/or non-intelligent mobile agents. The DAM model consists of communities of mobile and stationary intelligent agents in collaboration. We discuss an experiment with DAM and proceed to discuss outstanding research issues. The DAM approach uses the properties and characteristics of autonomic systems in support of managing service-oriented communications networks and protecting e-commerce and business enterprises against cyber terrorism.

Models of feedback and adaptation in multi-agent systems for disaster situation management

The response, rescue and recovery teams that are engaged in disaster management operations require a continuous and comprehensive information flow of the disaster environment and a situational awareness in order to undertake fast and coordinated actions. Because of highly dynamic and often unpredictable disaster situations the teams need to adjust their goals, resources and actions both on an individual member level (agent) and on an entire team level (multi-agent system). This paper investigates a new approach to an agents adaptability based on cognitive feedback introduced into the framework of inter-agent collaboration. The paper is a continuation of our work on situation-aware multi-agent systems. We discuss how agent adaptation and cognitive feedback is applied in the architecture of multi-agent systems for disaster situation management.