Enabling Distributed Cognitive Collaborations on the Semantic Web

Enabling Distributed Cognitive Collaborations on the Semantic Web

Amna Basharat (National University of Computer and Emerging Sciences, Pakistan) and Gabriella Spinelli (Brunel University, UK)
DOI: 10.4018/978-1-60566-650-1.ch031
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Abstract

To date research on improving the state of multi-agent collaboration has only focused on the provision of grounding tools, technologies, protocols, standards and infrastructures that drive the Semantic Web and agent architectures. The basic cognitive and interactional requirements of agents have been neglected leading to the current state-of-the-art development of the Semantic Web whereby its full potential is constrained by the rigid state of multi-agent collaboration. This chapter illustrates and discusses an alternative approach to the development of the agent mediated Semantic Web. The fundamental premise of our approach is that enhancing agents cognitive and interactional abilities is the key to make the digital world of agents more flexible and adaptive in its role to facilitate distributed collaboration. The novelty of this research is that it adapts cognitive models from HCI to develop a heuristic framework called Cognitive Modelling of Multi-Agent Action (COMMAA) for modeling agents’ actions in an attempt to provide an architecture that improves the flexibility of Multi-agent interaction by promoting cognitive awareness. The results of the evaluation show an improved flexibility, interoperability and reusability of agents’ collective behaviours and goals.
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Objectives Of The Chapter

The following chapter will serve the following aims and objectives:

  • Delineate upon the current limitations in the state of multi-agent collaboration in order to elaborate the rationale, need and the synergistic role of cognitive dimension to the Semantic Web with particular regard to distributed collaborations amongst agents

  • Describe the conceptual constituents of a theoretical framework called Cognitive Model of Multi-Agent Action (COMMAA) derived from cognitive models in HCI to improve the state of multi-agent collaboration

  • Detail upon the Design and Implementation of Semantic Representational and Ontological Models based on the theoretical principles of COMMAA that allow cognitive processing of an agents action using state of the art Semantic Web technologies

  • Describe heuristic reasoning mechanisms that can be derived from cognitive models to enhance the cognition of Semantic Web agents

  • Analyze and discuss the impact of using COMMAA to model multi-agent collaborative applications on the Semantic Web

Key Terms in this Chapter

Cognitive Profile: It is a semantic representation model which includes information about the cognitive states of an agent, its functional capacities and affordances.

Multi-Agent System: Multi-Agent System (MAS) is a distributed collaborative environment which allows a number of agents to cooperate and interact with other agents (including both people and software) that have possibly conflicting aims, in a complex environment.

Affordance: An affordance is a resource or support that the environment offers an agent for action, and that the agent can directly perceive and employ.

Capability: The functional ability possessed by an agent to achieve some given goal or requirement.

Cognitive Awareness: It refers to the ability of the Web agents to diagnose their processing limitations and to establish interactions with the external environment (in the form of other agents including humans and software agents).

Agent: Agents are defined as autonomous, problem-solving computational entities capable of effective operation in dynamic and open environments.

Cognitive Model: Internal representations of the current situation created by either a human and agent to assess their state with respect to the environment.

COMMAA (Cognitive Model of Multi-Agent Action): A framework for modeling agents’ actions and interactions in its environment in an attempt to provide an architecture that improves the flexibility of Multi-agent interaction by promoting cognitive awareness .

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