Artificial Intelligence Planning

author: Jussi Rintanen, NICTA

Description

The course presents the most important approaches to state space traversal used in planning, including techniques based on propositional satisfiability testing, heuristic state-space search, and logic-based data structures like binary decision diagrams. The main applications of these techniques in classical planning and in more complex forms of planning is discussed.

Categories

Top: Computer Science: Artificial Intelligence

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*Slides*
0:00	Automated Planning
0:19	What is planning? (1)
1:57	What is planning? (2)
3:30	Blocks world - The states
4:41	Blocks world - The transition graph for three blocks
6:24	Why is planning difficult? (1)
6:49	Why is planning difficult? (2)
7:18	Why is planning difficult? (3)
7:31	Transition systems
9:13	Representation of transition systems
11:46	Blocks world with Boolean state variables
14:21	Actions
18:47	Actions - Example
22:18	Actions - Active effects
23:47	Actions - The successor state of a state
25:53	Transition systems
26:32	Transition systems
26:47	Actions
26:51	Transition systems
27:55	Plans
29:09	Planning in the propositional logic
31:13	Actions as formulae
34:18	Representation of one event/action - Changes to state variables
37:21	Choice between actions/events
38:39	Existence of plans of length t
41:08	Planning as satisfiability - Example
46:11	Parallel plans
46:58	Representation of one event/action - Changes to state variables
47:05	Actions as formulae
47:19	Choice between actions/events
47:24	Parallel plans
48:10	Interpretation of parallelism
50:12	Interference - Example
51:56	Interference

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