AUSF Agent based User Simulation Framework Om Narayan.

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Presentation transcript:

AUSF Agent based User Simulation Framework Om Narayan

Outline

Introduction ➢ AUSF is a multiple agent based framework written in Python which provide basic infrastructure to simulate user activity in goal oriented community. ➢ This project started to overcome the traditional load testing. ➢ Over a period of time, it has evolved as a generic solution for user simulation requirements.

What are Agents? ➢ Software entities that assist people and act on their behalf – IBM ➢ An agent is a software component (object) which can perform one or more tasks in some predefined manner ➢ The term "agent" describes a software abstraction, an idea, or a concept, similar to OOP terms such as methods, functions, and objects The concept of an agent provides a convenient and powerful way to describe a complex software entity that is capable of acting with a certain degree of autonomy in order to accomplish tasks on behalf of its user. But unlike objects, which are defined in terms of methods and attributes, an agent is defined in terms of its behavior.... Wikipedia Wikipedia

Designing Smart Agents ➢ Autonomous ➢ Goal-directed ➢ Task-able ➢ Situated ➢ Cooperative ➢ Communicative ➢ Adaptive

Designing Smart Agents Autonomous An autonomous agent is a system situated in, and part of, an environment, which senses that environment, and acts on it, over time, in pursuit of its own agenda. This agenda evolves from drives (or programmed goals). The agent acts to change the environment and influences what it senses at a later time.... WikipediaWikipedia Pythonic Way : ➢ Process entity which have predefine Object stage. ➢ An independent process-of-control. ➢ Object stage can be over-ridden. ➢ Goal of Agent is set by process-controller.

Designing Smart Agents Goal-oriented Maintaining an agenda of goals which it pursues until accomplished or believed impossible Pythonic Way : ➢ All agents complete their life cycle by unregistering themselves. ➢ Other goals are driven by process-control server. ➢ Each Agents have task queue. ➢ End of the all every task agent should have to notify the status of goal to monitoring server. ➢ All agent complete their life cycle by unregistering them self.

Designing Smart Agents Task-able The agent acts to change one agent can delegate rights/actions to another Pythonic Way : ➢ Agent are capable to assign some task to other agent/s. ➢ An independent process-of-control. ➢ Object stage can be over-ridden. ➢ Task of Agent is set by process-controller.

Designing Smart Agents Situated In an environment (computational and/or physical) which it is aware of and reacts to Pythonic Way : ➢ Each agent has unique Id. ➢ Each agent's communities have its own process-controller. ➢ Agents are fully aware of it resource. ➢ Whenever agent initiated or changed its object stage, it also gets access to required resources.

Designing Smart Agents Cooperative With other agents (software or human) to accomplish its tasks. Pythonic Way : ➢ Agents can share their stage and task. ➢ Agents learn in co-operative manner ➢ In current mode agents share two layer of knowledge sharing. ➢ Local resource appearances. ➢ Global resource appearances. ➢ Agents achieved their goal.

Designing Smart Agents Communicative To make agents understand each other they have to not only speak the same language, but also have a common ontology. An ontology is a part of the agent's knowledge base that describes what kind of things an agent can deal with and how they are related to each other. … WikipediaWikipedia Pythonic Way : ➢ Its based on xmpp. ➢ Agent can send message to sever/Agents. ➢ Communication is based on text. ➢ Message is parse by Agents.

Designing Smart Agents Adaptive Modifying beliefs & behavior based on experience Pythonic Way : ➢ In current mode Agents adaptivity is based on 2 mode ➢ Resource mode : ➢ Master server stop sending particular commands after threshold limit based on the response analysis ➢ Knowledge mode ➢ Agents update common knowledge base

Agent on large scale More agent more work Pythonic Way : ➢ Agents are divided in grid way. ➢ All connected system can have their local controller server ➢ Agents are process and NOT thread.

Present and Future AULT : Agent based User simulation and Load Testing VICA : Virtual Intelligent Chatting Agent Pythonic Way : ➢ Programming model and APIs. ➢ Programming infrastructure and services. ➢ Naming scheme for servers, agents, resources Agent transfer protocol. ➢ Inter-agent communication protocol ➢ Debugging facilities.