Modeling and Verification of Agent based Adaptive Traffic Signal using Symbolic Model Verifier

This paper addresses the issue of modeling and verification of a Multi Agent System (MAS) scenario. We have considered an agent based adaptive traffic signal system. The system monitors the smooth flow of traffic at intersection of two road segment. After describing how the adaptive traffic signal system can efficiently be used and showing its advantages over traffic signals with predetermined periods, we have shown how we can transform this scenario into Finite State Machine (FSM). Once the system is transformed into a FSM, we have verified the specifications specified in Computational Tree Logic(CTL) using NuSMV as a model checking tool. Simulation results obtained from NuSMV showed us whether the system satisfied the specifications or not. It has also showed us the state where the system specification does not hold. Using which we traced back our system to find the source, leading to the specification violation. Finally, we again verified the modified system with NuSMV for its specifications.Comment: 13 pages, 6 figures, Submitted to International Journal of Computer Application (IJCA

Enabling Adaptive Grid Scheduling and Resource Management

Wider adoption of the Grid concept has led to an increasing amount of federated computational, storage and visualisation resources being available to scientists and researchers. Distributed and heterogeneous nature of these resources renders most of the legacy cluster monitoring and management approaches inappropriate, and poses new challenges in workflow scheduling on such systems. Effective resource utilisation monitoring and highly granular yet adaptive measurements are prerequisites for a more efficient Grid scheduler. We present a suite of measurement applications able to monitor per-process resource utilisation, and a customisable tool for emulating observed utilisation models. We also outline our future work on a predictive and probabilistic Grid scheduler. The research is undertaken as part of UK e-Science EPSRC sponsored project SO-GRM (Self-Organising Grid Resource Management) in cooperation with BT

Towards integrated island management: lessons from Lau, Malaita, for the implementation of a national approach to resource management in Solomon Islands: final report

Solomon Islands has recently developed substantial policy aiming to support inshore fisheries management, conservation, climate change adaptation and ecosystem approaches to resource management. A large body of experience in community based approaches to management has developed but “upscaling” and particularly the implementation of nation-wide approaches has received little attention so far. With the emerging challenges posed by climate change and the need for ecosystem wide and integrated approaches attracting serious donor attention, a national debate on the most effective approaches to implementation is urgently needed. This report discusses potential implementation of “a cost-effective and integrated approach to resource management that is consistent with national policy and needs” based on a review of current policy and institutional structures and examination of a recent case study from Lau, Malaita using stakeholder, transaction and financial cost analyses

Between Scylla and Charybdis: Environmental governance and illegibility in the American West

In The Odyssey, Odysseus and his crew must navigate the Strait of Messina between two great hazards: the six-headed monster Scylla on one side, and the whirlpool Charybdis on the other. This conceit here guides a critical engagement with scientific knowledge and state power, grounded in the positionality and practices of government agents charged with the management of controversial species and processes in the American West. Based in ethnographic and archival research on wolf-livestock conflict and public lands grazing in Central Idaho, I relate how agents with the U.S. Forest Service and Idaho Department of Fish and Game navigate conditions not of their own choosing. Sailing the “choppy seas” of complex systems and multiple-use mandates, with the “whirlpool” of cuts to capacity on one side and the “monster” of political controversy and litigation on the other, agents appear to collect less or more ambiguous information on their charges, resulting in a partial “blindness” or illegibility. Although a rational adaptation to unrealistic expectations, this ignorance is not bliss but rather symptom and source of dysfunction, limiting agents’ ability to carry out monitoring, collaboration, and effectively conduct on-the-ground management. Understanding patterns of illegibility requires that we attend both to broader contextual pressures and situated motivations. In so doing, we might account for the seeming disconnect between agencies’ stated aims and practices, complicate traditional assumptions of evidence-based scientific management and analyses of bureaucratic rationality and state power, and make sense of the apparent dysfunction around environmental governance in the American West today

Adaptive planning for distributed systems using goal accomplishment tracking

Goal accomplishment tracking is the process of monitoring the progress of a task or series of tasks towards completing a goal. Goal accomplishment tracking is used to monitor goal progress in a variety of domains, including workflow processing, teleoperation and industrial manufacturing. Practically, it involves the constant monitoring of task execution, analysis of this data to determine the task progress and notification of interested parties. This information is usually used in a passive way to observe goal progress. However, responding to this information may prevent goal failures. In addition, responding proactively in an opportunistic way can also lead to goals being completed faster. This paper proposes an architecture to support the adaptive planning of tasks for fault tolerance or opportunistic task execution based on goal accomplishment tracking. It argues that dramatically increased performance can be gained by monitoring task execution and altering plans dynamically

Context-Aware Information Retrieval for Enhanced Situation Awareness

In the coalition forces, users are increasingly challenged with the issues of information overload and correlation of information from heterogeneous sources. Users might need different pieces of information, ranging from information about a single building, to the resolution strategy of a global conflict. Sometimes, the time, location and past history of information access can also shape the information needs of users. Information systems need to help users pull together data from disparate sources according to their expressed needs (as represented by system queries), as well as less specific criteria. Information consumers have varying roles, tasks/missions, goals and agendas, knowledge and background, and personal preferences. These factors can be used to shape both the execution of user queries and the form in which retrieved information is packaged. However, full automation of this daunting information aggregation and customization task is not possible with existing approaches. In this paper we present an infrastructure for context-aware information retrieval to enhance situation awareness. The infrastructure provides each user with a customized, mission-oriented system that gives access to the right information from heterogeneous sources in the context of a particular task, plan and/or mission. The approach lays on five intertwined fundamental concepts, namely Workflow, Context, Ontology, Profile and Information Aggregation. The exploitation of this knowledge, using appropriate domain ontologies, will make it feasible to provide contextual assistance in various ways to the work performed according to a user’s taskrelevant information requirements. This paper formalizes these concepts and their interrelationships

Logic, self-awareness and self-improvement: The metacognitive loop and the problem of brittleness

This essay describes a general approach to building perturbation-tolerant autonomous systems, based on the conviction that artificial agents should be able notice when something is amiss, assess the anomaly, and guide a solution into place. We call this basic strategy of self-guided learning the metacognitive loop; it involves the system monitoring, reasoning about, and, when necessary, altering its own decision-making components. In this essay, we (a) argue that equipping agents with a metacognitive loop can help to overcome the brittleness problem, (b) detail the metacognitive loop and its relation to our ongoing work on time-sensitive commonsense reasoning, (c) describe specific, implemented systems whose perturbation tolerance was improved by adding a metacognitive loop, and (d) outline both short-term and long-term research agendas