Verifying space and time requirements for resource-bounded agents

agent

Verifying Space and Time Requirements for Resource-Bounded Agents

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Verifying space and time requirements for resource-bounded agents

The effective reasoning capability of an agent can be defined as its capability to infer, within a given space and time bound, facts that are logical consequences of its knowledge base. In this paper we show how to determine the effective reasoning capability of an agent with limited memory by encoding the agent as a transition system and automatically verifying whether a state where the agent believes a certain conclusion is reachable from the start state. We present experimental results using the Model Based Planner (mbp) which illustrates how the length of the deduction varies for different memory sizes

A formal approach to modelling and verification of context-aware systems

The evolution of smart devices and software technologies has expanded the domain of computing from workplaces to other areas of our everyday life. This trend has been rapidly advancing towards ubiquitous computing environments, where smart devices play an important role in acting intelligently on behalf of the users. One of the sub fields of the ubiquitous computing is context-aware systems. In context-aware systems research, ontology and agent-based technology have emerged as a new paradigm for conceptualizing, designing, and implementing sophisticated software systems. These systems exhibit complex adaptive behaviors, run in highly decentralized environment and can naturally be implemented as agent-based systems. Usually context-aware systems run on tiny resource-bounded devices including smart phones and sensor nodes and hence face various challenges. The lack of formal frameworks in existing research presents a clear challenge to model and verify such systems. This thesis addresses some of these issues by developing formal logical frameworks for modelling and verifying rule-based context-aware multi-agent systems. Two logical frameworks LOCRS and LDROCS have been developed by extending CTL* with belief and communication modalities, which allow us to describe a set of rule-based context-aware reasoning agents with bound on time, memory and communication. The key idea underlying the logical approach of context-aware systems is to define a formal logic that axiomatizes the set of transition systems, and it is then used to state various qualitative and quantitative properties of the systems. The set of rules which are used to model a desired system is derived from OWL 2 RL ontologies. While LOCRS is based on monotonic reasoning where beliefs of an agent cannot be revised based on some contradictory evidence, the LDROCS logic handles inconsistent context information using non-monotonic reasoning. The modelling and verification of a healthcare case study is illustrated using Protégé IDE and Maude LTL model checker

Reasoning about resource-bounded multi-agent systems

The thesis presents logic-based formalisms for modelling and reasoning about resource-bounded multi-agent systems. In the field of multi-agent system, it is well-known that temporal logics such as CTL and ATL are powerful tools for reasoning about multi-agent systems. However, there is no natural way to utilise these logics for expressing and reasoning about properties of multi-agent systems where actions of agents require resources to be able to perform. This thesis extends logics including Computational Tree Logic (CTL), Coalition Logic (CL) and Alternating-time Temporal Logic (ATL) which have been used to reasoning about multi-agent systems so that the extended ones have the power to specify and to reason about properties of resource-bounded multi-agent systems. While the extension of CTL is adapted for specifying and reasoning about properties of systems of resource-bounded reasoners where the resources are explicitly memory, communication and time, the extensions of CL and ATL are generalised so that any resource-bounded multi-agent system can be modelled, specified and reasoned about. For each of the logics, we describe the range of resource-bounded multi-agent systems they can account for and axiomatisation systems for reasoning which are proved to be sound and complete. Moreover, we also study the satisfiability problem of these logics

Reasoning about resource-bounded multi-agent systems

The thesis presents logic-based formalisms for modelling and reasoning about resource-bounded multi-agent systems. In the field of multi-agent system, it is well-known that temporal logics such as CTL and ATL are powerful tools for reasoning about multi-agent systems. However, there is no natural way to utilise these logics for expressing and reasoning about properties of multi-agent systems where actions of agents require resources to be able to perform. This thesis extends logics including Computational Tree Logic (CTL), Coalition Logic (CL) and Alternating-time Temporal Logic (ATL) which have been used to reasoning about multi-agent systems so that the extended ones have the power to specify and to reason about properties of resource-bounded multi-agent systems. While the extension of CTL is adapted for specifying and reasoning about properties of systems of resource-bounded reasoners where the resources are explicitly memory, communication and time, the extensions of CL and ATL are generalised so that any resource-bounded multi-agent system can be modelled, specified and reasoned about. For each of the logics, we describe the range of resource-bounded multi-agent systems they can account for and axiomatisation systems for reasoning which are proved to be sound and complete. Moreover, we also study the satisfiability problem of these logics

A formal approach to modelling and verification of context-aware systems

The evolution of smart devices and software technologies has expanded the domain of computing from workplaces to other areas of our everyday life. This trend has been rapidly advancing towards ubiquitous computing environments, where smart devices play an important role in acting intelligently on behalf of the users. One of the sub fields of the ubiquitous computing is context-aware systems. In context-aware systems research, ontology and agent-based technology have emerged as a new paradigm for conceptualizing, designing, and implementing sophisticated software systems. These systems exhibit complex adaptive behaviors, run in highly decentralized environment and can naturally be implemented as agent-based systems. Usually context-aware systems run on tiny resource-bounded devices including smart phones and sensor nodes and hence face various challenges. The lack of formal frameworks in existing research presents a clear challenge to model and verify such systems. This thesis addresses some of these issues by developing formal logical frameworks for modelling and verifying rule-based context-aware multi-agent systems. Two logical frameworks LOCRS and LDROCS have been developed by extending CTL* with belief and communication modalities, which allow us to describe a set of rule-based context-aware reasoning agents with bound on time, memory and communication. The key idea underlying the logical approach of context-aware systems is to define a formal logic that axiomatizes the set of transition systems, and it is then used to state various qualitative and quantitative properties of the systems. The set of rules which are used to model a desired system is derived from OWL 2 RL ontologies. While LOCRS is based on monotonic reasoning where beliefs of an agent cannot be revised based on some contradictory evidence, the LDROCS logic handles inconsistent context information using non-monotonic reasoning. The modelling and verification of a healthcare case study is illustrated using Protégé IDE and Maude LTL model checker