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Seminar: Advanced Topics in AI Planning - Topics

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Area A: Symbolic Planning

A1: Transition Trees for Cost-Optimal Symbolic Planning

Betreuer: Dr. David Speck

  • Transition Trees for Cost-Optimal Symbolic Planning (PDF)

A2: Symbolic Heuristic Search using Decision Diagrams

Betreuer: Dr. David Speck

  • Symbolic Heuristic Search using Decision Diagrams (PDF)

A3: Relaxed exists-step encoding

Betreuer: Dr. Gregor Behnke

  • Planning as Satisfiability with Relaxed ∃-Step Plans (PDF)

A4: Planning with Axioms

Betreuer: Dr. David Speck

  • In Defense of PDDL Axioms (PDF)
  • Optimal Planning with Axioms (PDF)

Area B: Epistemic Planning

B1: Epistemic Planning as Classial Planning

Betreuer: Dr. Thorsten Engesser

  • Beliefs In Multiagent Planning: From One Agent to Many (PDF)

B2: Formula-Based Epistemic Planning

Betreuer: Dr. Thorsten Engesser

  • Planning Over Multi-Agent Epistemic States: A Classical Planning Approach (PDF)

B3: DEL-Based Epistemic Planning

Betreuer: Dr. Thorsten Engesser

  • Epistemic planning for single and multi-agent systems (PDF)
  • Don't Plan for the Unexpected: Planning Based on Plausibility Models (PDF)

Area C: Multi-Agent Path Finding (MAPF)

C1: MAPF variations and algorithms

Betreuer: Prof. Dr. Bernhard Nebel

  • AI Buzzwords Explained: Multi-Agent Path Finding (MAPF) (PDF)
  • Search-Based Optimal Solvers for the Multi-Agent Pathfinding Problem: Summary and Challenges (PDF)

C2: MAPF reduced to SAT

Betreuer: Prof. Dr. Bernhard Nebel

  • Efficient SAT Approach to Multi-Agent Path Finding under the Sum of Costs Objective (PDF)

C3: Online Multi-Agent Pickup and Delivery via Token Passing

Betreuer: Rolf-David Bergdoll

  • Lifelong Multi-Agent Path Finding for Online Pickup and Delivery Tasks (PDF)

C4: Persistent and Robust Execution of Multi-Agent Pickup and Delivery

Betreuer: Rolf-David Bergdoll

  • Persistent and Robust Execution of MAPF Schedules in Warehouses (PDF)

Area D: Multi-Agent Planning

D1: Privacy Preserving Multi-Agent Planning

Betreuer: Patrick Caspari

  • Privacy Preserving Multi-Agent Planning with Provable Guarantees (PDF)

D2: Multi-Agent Planning as Satisfiability

Betreuer: Patrick Caspari

  • mu-SATPLAN - Multi-agent planning as satisfiability (PDF)

Area E: Probabilistic Planning

E1: Probabilistic Planning via Determinization in Hindsight

Betreuer: Grigorios Mouratidis

  • Probabilistic Planning via Determinization in Hindsight (PDF)

E2: Probabilistic Planning Based on UCT

Betreuer: Grigorios Mouratidis

  • PROST Probabilistic Planning Based on UCT (PDF)

E3: Probabilistic Logic Programming

Betreuer: Dr. Tim Schulte

  • Markov Descision Processes Specified by Probabilistic Logic Programming: Representation and Solution (PDF)

E4: Privacy-preserving Planning in Stochastic Environments

Betreuer: Dr. Tim Schulte

  • Privacy-preserving Planning in Stochastic Environments (PDF)

Area F: Related Problems

F1: Proving (and Certifying) Unsolvability

Betreuer: Dr. Robert Mattmüller

  • Unsolvability Certificates for Classical Planning (PDF)
  • A Proof System for Unsolvable Planning Tasks (PDF)
  • Certifying Planning Systems: Witnesses for Unsolvability (PDF)
  • Tutorial: Certified Unsolvability in Classical Planning (PDF)

F2: Generalized Planning

Betreuer: Dr. Robert Mattmüller

  • A review of generalized planning (PDF)

F3: Action Model Acquisition

Betreuer: Dr. Robert Mattmüller

  • Classical Planning in Deep Latent Space: Bridging the Subsymbolic-Symbolic Boundary (PDF)

F4: Complexity of h^+ heuristics in HTN Planning

Betreuer: Dr. Gregor Behnke

  • On the Feasibility of Planning Graph Style Heuristics for HTN Planning (PDF)

F5: Hierarchical Planning via Translation to Classical Planning

Betreuer: Dr. Gregor Behnke

  • Translating HTNs to PDDL: A Small Amount of Domain Knowledge Can Go a Long Way (PDF)