• to formulate the task of planning of abstract actions as a dynamic component of the intelligent behaviour of an artificial agent, capable of solving different problems using explicit representation of knowledge about the environment;
• to introduce the different approaches to planning with examination of the differ-ent problems which should be controlled for correct planning of the agent behaviour;
• to examine the complexity of the task of planning in the different formulations and the possibilities for extension towards a more realistic planning.

• demonstrate familiarity with the basic conceps and methods for planning;
• implement planning algorithms.

Advanced Topics in AI, Berlin: Springer Verlag (1988).

Wilkins, D.,

Practical Planning: Extending the Classical AI Planning Paradigm, San Mateo, CA: Morgan Kaufmann (1988).

Allen, J., Kautz, H., Pelavin, R., Tenenberg, J.,

Reasoning about Plans, Los Altos, CA: Morgan Kaufmann (1991).

• introduction - basic concepts, philosophical and computer science point of view on planning, taxonomy of actions and agents
• classical planning paradigm and taxonomy of methods for classical planning
• planning in time with accounting of action duration
• non-classical planning and methods for planning of actions in distributed, coop-erative and evolving environment

Introduction to Planning

Topic 1: The task for planning of actions. Planning as a dynamic component of the rational behaviour. Taxonomy of actions - mental, verbal, motor actions, and time changes; active and reactive agents. AI planning problems: representation, inference, control. Frame problem, qualifica-tion problem, prediction, persistence. Complexity.

Topic 2: Classical AI Planning Problem. Basic concepts of the state-space ap-proach to planning: goal state, initial state, state changes and action se-quencing. Precondition-effects model of actions. Planning as search. Means-ends analisys. GPS.

Methods for Planning of Change

Topic 3:Linear planning. Deductive planning. Green algorithm.Situation calcu-lus. Goal regression, progression of knowledge and digression methods. Non-monotonicity of knowledge and its representations. Frame axioms and complexity of the changes. STRIPS approach to coping with non-monotonicity.

Topic 4: Hierarchical Planning. Abstraction in planning. Sequencing and macrooperators. Abstraction levels and abstraction barriers. Control over granularity. AbSTRIPS, TWEAK.

Topic 5: Non-linear planning. Goal interaction and action dependencies. Resolving of conflicts. Least commitment principle. Labelling and propagation of markers. NONLIN, NOAH, and SIPE.

Lab work:Experiments with the computer simulation: AbSTRIPS-like planner.

Topic 6: Planning with constraints. Linear, nonlinear and hierarchical con-straints. Constraint satisfaction and constraint propagation. Stepwise refinement.

Topic 7: Meta-planning. Hierarchy of actions, hierarchy of changes and hierar-chy of plans. Meta-planning and reflection. MOLGEN.

Seminar:Discussing of the classical dynamic planning algorithms.

Topic 8: Logical Models of Dynamics. Situation calculus vs. Dynamic logics vs. Hoare logics. Complexity of inference. Classroom Exercises: Formal evaluation of the complexity of planning tasks in differ-ent specificational languages.

Methods for Planning in Time.

Topic 9:Planning within Time Limits. Time indexation scheme and time win-dowing. DEVISOR. Planning with satisfaction of temporal constraints. Dean's approach.

Topic 10: Logical Models of Time.Point-based, interval-based, and event-based models. Linear and branching time. Complexity of reasoning about time.

Classroom exercises: Formal evaluation of the complexity of the temporal planning task in different specificational languages.

Topic 11: Temporal Planning with Time Prediction. Changes in the future, in the next moment and continuing changes. Temporal necessity and temporal possibility. McDermott's planner.

Topic 12: Interval-Based Temporal Planning. Events and processes. Duration of actions. Continuing possibility and continuing necessity. Allen's plan-ner.

Topic 13: Event-Based Temporal Planning. Events and situations. History of events and event triggering. Cooperative events and parallel actions. Lansky's planner.

Seminar:Discussing of the temporal methods for planning.Methods for Non-Classical Planning.

Topic 14: Distributed Planning. Action blackboard and plan agenda. Independent and dependent knowledge sources. Control over the planning process. Critics and plan corrections.

Topic 15: Reactive planning. Pros and cons of deterministic planning. Replanning during execution. Prediction vs. experimentation in planning. Genetic, evolutionary and chaotic planning.

Lab work: Experimental evaluation of the planning strategies using planning workbench (Truckworld, Tileworld, Mice).