feasibility criteria for investigating potential application areas of ai planning t.l.mccluskey, the...

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Feasibility Criteria for Investigating Potential Application Areas of AI Planning T.L.McCluskey, The University of Huddersfield,UK Email [email protected]

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Feasibility Criteria for Investigating Potential Application Areas of AI Planning

T.L.McCluskey,

The University of Huddersfield,UK

Email [email protected]

Knowledge Engineering and Intelligent Interfaces

Automated Planning Technology

..reasons with EXPLICIT representations of actions, constraints, goals ..

in order to synthesise plans and schedules

Sounds like it would be widely applicable software?

A

B

B

A

Knowledge Engineering and Intelligent Interfaces

Summary of Talk

Specialised Commercial

Applications of Planning

Generalised Application within

an “Agent” or as a “Service”

?

?

Knowledge Engineering and Intelligent Interfaces

Related Work

Evaluation Criteria similar in parts to ANY introduction of (advanced) technology, especially introduction of IKBS

However – our work is much more specific within application area, and technology being introduced

Past applications of AI Planning tend to skirt around issues of feasibility – they are a successful application already!

Knowledge Engineering and Intelligent Interfaces

Applications considered

1. Air Traffic Control (old one)

2. Water / Flood Management

3. Road Traffic Management

Knowledge Engineering and Intelligent Interfaces

Air Traffic Management

Knowledge Engineering and Intelligent Interfaces

Air Traffic ManagementProblem:Hundreds of Flights over North Atlantic every day, these have to be planned the day before, then re-planned ½ hour before plane entry if a conflict probe shows a potential problem.

two potential applications of AI planning:

- Advanced (day before) flight planning-En Route planning

Actions include feasible aircraft movementGoals are (a) safety – not violating conflict zones (b) fuel efficiency and passenger comfort

Knowledge Engineering and Intelligent Interfaces

Water / Flood Management

GIS tool from ESRI

Knowledge Engineering and Intelligent Interfaces

Water / Flood Management involves local and national authorities, service industries, and research

institutes.

two potential applications of AI planning:

for long term planning of infrastructure to prevent or lessen the risk of flooding - climatic change and population change, and may involve flood defence design or even river design

for real-time planning to support flood event management. - under the heading of crisis management, and may incorporate evacuation management.

Actions in the latter include movement of evacuation assets, deployment of emergency service, and information acquisition and information dissemination

Goals would involve minimising the loss of life and property

Knowledge Engineering and Intelligent Interfaces

Road Network Management

Complex data gathering, knowledge extraction, planning and control application

Critical to congestion control, incident management, road use optimisation

Knowledge Engineering and Intelligent Interfaces

Road Traffic Management many systems for data gathering (various types of traffic detectors, cctv)

Many organisations and regulatory bodies involved (complex set of stakeholders)

potential application of AI planning:

for day to day, event and crisis planning

Actions include traffic lights, variable speed limits, variable message signs, local radio, satnav

Goal: to form and execute a plan to control and hence optimise the network

Knowledge Engineering and Intelligent Interfaces

A proposed system architecture

Knowledge Engineering and Intelligent Interfaces

Is the Application of AI Planning Feasible? Evaluation Criteria1.Motivation Factors

1. cost savings?

2. quality of service?

2.Technological Context and Human Factors

1. Existing technological infrastructure

2. Data availability, form, quality (both real-time AND historical)

3. Acceptance of Innovation by Users

3.Knowledge Engineering Factors

1. Closeness to previous applications

2. Procedure formalisation in the problem area

3. Appropriateness for AI planning solution

Knowledge Engineering and Intelligent Interfaces

Evaluation: Air Traffic Management1.Motivation Factors [FAIL] Unclear that the innovation would improve current system ‘intelligent’ systems not embraced quickly because of safety critical

nature of tasks

2.Technological Context and Human Factors [PASS] Data availability excellent Few current systems, all reasonably interoperable, but systems for

different areas (Oceanic, Domestic) Record of technological innovation patchy

3.Knowledge Engineering Factors [PASS] Excellent as we had already produced a formal model of the

environment and separation criteria in previous work! Planning problem fairly straightforward if a little numerical

Knowledge Engineering and Intelligent Interfaces

Evaluation: Flood Event Management

1.Motivation Factors [PASS] the production of sound plans in real time which are higher quality than

human produced (human track record not good) pre-event generation of emergency plans is infeasible (FLOODsite EU

project)

2.Technological Context and Human Factors [PASS] use of DSS systems quality of data (eg satnav) good, and flood simulation/prediction good Human acceptance of technology good, but users not tech experts

3.Knowledge Engineering Factors [BORDERLINE] past work: evacuation/crisis management fairly well researched complex planning problem involving continuous processes and

uncertainty

Knowledge Engineering and Intelligent Interfaces

Evaluation: Road Traffic Management

1.Motivation Factors [pass] with complex data, goals, actions, RTM is becoming too

complicated for human control? road management experts scarce2.Technological Context and Human Factors [pass] AI systems already deployed in Transport eg Scoot culture of technological innovation excellence amounts of historical data and experimental

platforms But many different systems, not all interoperable3.Knowledge Engineering Factors [borderline] road strategies / plans semi-formalised some similar benchmark planning domains but not on the

huge scale of a road network

Knowledge Engineering and Intelligent Interfaces

Summary

It is very difficult to find specialised application areas for automated planning – either conditions have to be just right OR a lot of extra effort is needed and the application is not (in the short run) cost effective.

.. AI Planning would be better off embedded within services