Combining Constraint-based and Classical Formulations for Encoding Planning Domains: GIPO IV Lee McCluskey Artform Research Group, Univ Huddersfield Email:

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Combining Constraint-based and Classical Formulations for Encoding Planning Domains: GIPO IV Lee McCluskey Artform Research Group, Univ Huddersfield No – read the paper! New Title: From Zero to the Briefcase World in 15 minutes

Artform Research Group GIPO Demonstration - To attempt to do something NO-ONE has ever done before during a (public) lecture …. Create a planning application form scratch …. GIPO:

Artform Research Group Background - Knowledge Engineering is key to the success of applications of AI Planning because of the need to encode and maintain structural, dynamic and heuristic knowledge about dynamical systems - The difficulty in evaluating and measuring knowledge engineering methods and tools is holding back their development – hence problems in ICKEPS, the new competition in Knowledge Engineering for AI Planning and Scheduling - This demo is an example of a new form of evaluation (not far from HCI’s keystroke model) – measuring KE tools on their encoding efficiency with well known applications using “experts” to encode them

Artform Research Group The “Briefcase” World – a simple logistics example Locations Things Bags

Artform Research Group putin(briefcase,home,cake) move(briefcase,home,work) takeout(briefcase,work,cake) move(briefcase,work,town) putin(briefcase,town,letter) move(briefcase,town,work) putin(briefcase,work,tools) move(briefcase,work,home) takeout(briefcase,home,tools) INITIAL STATE GOAL PLAN The planning function requires a planner a knowledge base and a specification of the tasks

Artform Research Group Summary - Using GIPO III one can produce a bugless briefcase world in a few minutes - Future work: Ghallab et al’s dockworkers world in 30 minutes, Univ Marylands’s logistics domain in 60 minutes ;-)