Constructing the Future with Intelligent AgentsConstructing the Future with Intelligent Agents

Raju Pathmeswaran

Dr Vian Ahmed

Prof Ghassan Aouad

Today's presentationToday's presentation

Aim of the research Introduction to agents Abilities of intelligent agents Types of agents configuration Example industrial adoptions Application of agents in construction Future trends

AimAim

Aim of this research is to investigate the extent to which we can develop and use intelligent agents to evaluate designs from multiple perspectives and under various scenarios

ScopeScope

nD Modelling Environment

Intelligent Agents

Decision Making Failure Prediction

Site Safety Hazard Detection

Design Model s Assembly Sequence

Site Layouts Design Query

Rule B ased System Knowledge Repository

Reasoner Ontology

Services Oriented Architecture

What is an agent?What is an agent?

An agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through effectors.

Some agentsSome agents

Human agent – eyes, ears, other organs for sensors; hands, legs etc for effectors

Robot agent – camera, infrared for sensors; various motors for effectors

Software agent – encoded bit strings as its percepts and actions

What is an intelligent agent?What is an intelligent agent?

An intelligent agent is a computer system that is capable of flexible autonomous action in order to meet its design objectives. responsive: agents should perceive their environment

and respond in a timely fashion to changes that occur in it

proactive: agents should not simply act in response to their environment, they should be able to exhibit opportunistic, goal-directed behaviour and take the initiative where appropriate

social: agents should be able to interact, when they deem appropriate, with other artificial agents and humans in order to complete their own problem solving and to help others with their activities.

What do agents have to offer?What do agents have to offer?

the ability to solve problems that have been beyond the scope of automation: either because no existing technology could be used

to solve the problem, or because it was considered too expensive (difficult,

time-consuming, risky) to develop solutions using existing technology;

the ability to solve problems that can already be solved in a significantly better (cheaper, more natural, easier, more efficient, or faster) way.

Belief-Desire-Intention (BDI) Belief-Desire-Intention (BDI) model of agencymodel of agency

Some philosophical basis in the Belief-Desire-Intention theory of human practical reasoning

Belief - informational state of the agent i.e. beliefs about the world including itself & other agents

Desire - motivational state of the agent i.e. objectives or situations that agent would like to accomplish

Intention - deliberative state of the agent i.e. what the agent has chosen to do

Agents Configurations

1. Agents based simulations1. Agents based simulations

1. Applications1. Applications

Healthcare Simulations Traffic Simulations Modelling Human Behaviour

2. Agents based real-world2. Agents based real-world

2. Applications2. Applications

Location based services Measurement of work-in-progress Security

3. Agents based adaptive 3. Agents based adaptive information systemsinformation systems

3. Applications3. Applications

Decision support systems E-commerce systems Financial systems e.g. anti money

laundering

Agent development toolkitsAgent development toolkits

The JADE (Java Agent Development Environment) is an open source platform that develops Java agents

JACK - operates on top of the Java programming language, acting as an extension of object-oriented development that provides agent-related concepts.

IMPACT provides an agent development environment, called AgentDE, that allows developers to define every aspect of the agent that forms part of the agent wrapper

Agent toolkits cont.Agent toolkits cont.

JACK makes use of just TCP and UDP for communication

IMPACT and JADE make use of RMI which is costly

Current trend is towards more lightweight approaches Web Service technologies beginning to play

an important role

Industrial adoption of agent Industrial adoption of agent based technologies based technologies

Manufacturing Control Daimler Chrysler demonstrated very high flexibility, increased

throughput, robustness and reliability of the agent-based manufacturing facility

Logistics and Supply Chains ABX use agent-based solution in order to (i) achieve

performance scalability, (ii) reflect the geographical distribution of the nodes, (iii) provide local re-planning without the need to rebuild the whole plan and (iv) increase robustness so that a single point of failure would be avoided

Production Planning Simulation Unmanned Aerial Vehicle control Space Exploration Applications

Intelligent agents in Intelligent agents in construction researchconstruction research

Collaborative design of structures (Anumba et al, 2002)

Designing steel skeleton structures of tall buildings (Skolicki and Kicinger, 2002)

Supporting construction procurement negotiation (Dzeng and Lin, 2004)

Constructing the future trendsConstructing the future trends

Simulation: potential of wider deployment of multi-agent systems in the field of simulation. E.g. Healthcare simulation

Prototyping: Agents enabled virtual prototyping; to identify design errors

Hardware: E.g. agent applications linked to the utilisation of RFID technology for construction materials and equipments

EndEnd

Thankyou