Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Towards requirements-driven information systems engineering: the Tropos project
Information Systems - The 13th international conference on advanced information systems engineering (CAiSE*01)
Tropos: An Agent-Oriented Software Development Methodology
Autonomous Agents and Multi-Agent Systems
A goal-driven and agent-based requirements engineering framework
Requirements Engineering
Quantifying Non-Functional Requirements: A Process Oriented Approach
RE '04 Proceedings of the Requirements Engineering Conference, 12th IEEE International
Using adaptive neuro-fuzzy inference system for hydrological time series prediction
Applied Soft Computing
The role of domain knowledge representation in requirements elicitation
SE'07 Proceedings of the 25th conference on IASTED International Multi-Conference: Software Engineering
Evaluation of Agent Oriented Requirements Engineering Frameworks
CSSE '08 Proceedings of the 2008 International Conference on Computer Science and Software Engineering - Volume 02
Expert Systems with Applications: An International Journal
Big five patterns for software engineering roles using an ANFIS learning approach with RAMSET
MICAI'10 Proceedings of the 9th Mexican international conference on Artificial intelligence conference on Advances in soft computing: Part II
A Takagi-Sugeno type neuro-fuzzy network for determining child anemia
Expert Systems with Applications: An International Journal
Autonomous Agents and Multi-Agent Systems
A framework for patterns in gaia: a case-study with organisations
AOSE'04 Proceedings of the 5th international conference on Agent-Oriented Software Engineering
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
An agent-oriented meta-model for enterprise modelling
ER'05 Proceedings of the 24th international conference on Perspectives in Conceptual Modeling
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Inter-agent communication is one of the main concerns of Agent Oriented Requirements Engineering (AORE). The concern is delineated as managing inter-dependencies and interaction among various agents performing collaborative activities. To carry out cooperative activities, the application areas viz. electronic commerce and enterprise resource planning in the distributed environment require an agent to predict and customize dependency needs termed as Degree of Dependency (DoD) so that the goal may be obtained within resource constraints and with optimal number of agents. To quantify and predict exertion load of an agent within resource constraints, this paper proposes an Analytical Inference Model (AIM) that would facilitate the developer to evaluate and envisage DoD and hence analyze the optimum number of agents to obtain predicted DoD. In this work, Adaptive Neuro Fuzzy Inference System (ANFIS) combining the potential benefits of Artificial Neural Network (ANN) and Fuzzy Logic (FL) is employed to discover the linear relationship in input domain attributes and DoD. The resultant optimization of exertion loads would immensely improve the quality of the Multi-Agent System. The hybrid, as well as back propagation learning algorithm, is employed to adapt from training data. The bestfitness of proposed model against test data is examined by the performance indicators-Coefficient of Correlation (CORR) and the Normalized Root Mean Square Error (NRMSE). It is observed that hybrid learning algorithm outperforms the back propagation algorithm.