PlanSIG, Dec, Temporal Plans and Resource Management Pieter Buzing & Cees Witteveen Delft University of Technology

PlanSIG, Dec, What about? Temporal planning in multi-agent systems or: distributed issues in planning systems Plan repair (during tactical phase) Introduce resource-based view Use scheduling heuristic Integrate it with multi agent temporal planning

PlanSIG, Dec, The Problem Many complex environments need planning and coordination of actions Example: airport, harbor, factory, … Multiple (autonomous) parties involved Issues: conflicting goals, communication, coordination Execution phase is error-prone: Environment is unpredictable, partial information

PlanSIG, Dec, Example: Airport

PlanSIG, Dec, Solution Requirements Respect individual planning tools: Abstract temporal plan model Handle aberrations during plan execution: Flexibility encoded in plan Respect and use agents’ intelligence: No central planner Smart coordination (negotiation)

PlanSIG, Dec, [10, 20] [15, 25][5, 20][14, 20] [8, 23][13, 26] [12, 21][15, 16] [10, 15] [12, 20] [7, 21] [10, 15] [10, 12] [8, 30] [12, 25] [11, 15] [5, 24] [7, 15] [10, 40] [12, 35] [8, 30] [1, 10] [5, 10] [5, 30] [10, 21] [10, 20] [4, 6] [5, 15] [5, 20] [5, 25]

PlanSIG, Dec, Simple Temporal Problem (STP) Planning as CSP (Dechter et.al., 1991) Temporal constraints between time point variables Path consistency = arc consistency = polynomial time: O(n^3) Extracting schedule is simple (read all lower bounds) Flexibility is maintained

PlanSIG, Dec, STPs and Preferences Duration action A is [10, 40]: hard constraint In practice: “A takes about 25 minutes, perhaps bit more/less” “25 would be ideal, but [15-30] is okay” Soft constraint expressed as preference function Repair opportunities

PlanSIG, Dec, Preferences and Repair During planning: Iteratively solve STPs at increasing p-levels “Best plan” is selected During execution: Some disruption causes a constraint change Return to less-preferred (but feasible) STP Example: Scheduled duration action A at p=3 is [23, 25] Oops! Action A will take 28 minutes: conflict! But we have a backup solution at p=1

PlanSIG, Dec, STPs and Resources Planning = action ordering Scheduling = resource assignment Practical planning problems are mix of both… Airport: gates, runways, taxiways Example: 4 flights scheduled on 2 gates

PlanSIG, Dec, [10, 20] [15, 25][5, 20][14, 20] [8, 23][13, 26] [12, 21][15, 16] [10, 15] [12, 20] [7, 21] [10, 15] [10, 12] [8, 30] [12, 25] [11, 15] [5, 24] [7, 15] [10, 40] [12, 35] [8, 30] [1, 10] [5, 10] [5, 30] [10, 21] [10, 20] [4, 6] [5, 15] [5, 20] [5, 25]

PlanSIG, Dec, [10, 20] [15, 25][5, 20][14, 20] [8, 23][13, 26] [12, 21][15, 16] [10, 15] [12, 20] [7, 21] [10, 15] [10, 12] [8, 30] [12, 25] [11, 15] [5, 24] [7, 15] [10, 40] [12, 35] [8, 30] [1, 10] [5, 10] [5, 30] [10, 21] [10, 20] [4, 6] [5, 15] [5, 20] [5, 25]

PlanSIG, Dec, [10, 20] [15, 25][5, 20][14, 20] [8, 23][13, 26] [12, 21][15, 16] [10, 15] [12, 20] [7, 21] [10, 15] [10, 12] [8, 30] [12, 25] [11, 15] [5, 24] [7, 15] [10, 40] [12, 35] [8, 30] [1, 10] [5, 10] [5, 30] [10, 21] [10, 20] [4, 6] [5, 15] [5, 20] [5, 25]

PlanSIG, Dec, Scheduling Heuristic for STPs Known scheduling heuristic: flexibility Amount of slack Planning phase: assign action a to resource s.t. flex(a) is max Plan repair: Choose action a s.t. flex(a) is min Move a to resource s.t. flex(a)’ becomes max

PlanSIG, Dec, Example (Gate Scheduling) Aircraft has delay: can not dock before t=50 Inconsistency since flex value is negative Find gate with highest flex: g2 Move aircraft to that gate

PlanSIG, Dec, Conclusion Trying to bring together: Multi agent system (temporal) Planning Scheduling aspects Application: Collaborating with NLR (National Aerospace Laboratory) Extending airport simulator with MA tools

PlanSIG, Dec,

PlanSIG, Dec, Choices in STPs “either action A before B or action B before A” Disjunctive Temporal Problem MA voting protocol for decision making (B&W, 2004b) Reordering actions as a means of plan repair