Author: Guzmán-Álvarez, César A. @cguz
Advisor: Eva Onaindia
Collaborator: Jeremy Frank
The present repository contains the source code of the (single agent) Reactive Planner (RP) of the Ph.D. dissertation entitled Reactive plan execution in multi-agent environments.
The RP allows execution agents to reactively and collaboratively attend a plan failure during execution. Specifically, it is a collaborative RP that employs bounded-structures to respond in a timely fashion to a somewhat dynamic and unpredictable environment.
The Multi-Agent RP allows execution agents to perform a general model, which enables a group of two agents to act coherently, overcoming the uncertainties of complex, dynamic environments to repair failures or inconsistent views of the world state.
We propose an architecture that comprises a general reactive planning and execution model that endows a single-agent with monitoring and execution capabilities. The model also comprises a reactive planner module that provides the agent with fast responsiveness to recover from plan failures. Thus, the mission of an execution agent is to monitor, execute and repair a plan, if a failure occurs during the plan execution.
The reactive planner builds on a time-bounded search process that seeks a recovery plan in a solution space that encodes potential fixes for a failure. The agent generates the search space at runtime with an iterative time-bounded construction that guarantees that a solution space will always be available for attending an immediate plan failure. Thus, the only operation that needs to be done when a failure occurs is to search over the solution space until a recovery path is found. We evaluated the performance and reactiveness of our single-agent reactive planner by conducting two experiments. We have evaluated the reactiveness of the single-agent reactive planner when building solution spaces within a given time limit as well as the performance and quality of the found solutions when compared with two deliberative planning methods.
The folder "src" contains the code of the reactive planner in Java. It is executable only for a single agent.
Please, if something fails or is missing email me : cguzman at cguz dot org.
The whole work of this thesis have led to a series of publications, which we referenced throughout the memory. Of these, the following stand out:
- Cesar Guzman, Pablo Castejon, Eva Onaindia, and Jeremy Frank. Reactive execution for solving plan failures in planning control applications. Journal of Integrated Computer-Aided Engineering, 22(4):343–360, 2015.
- Cesar Guzman, Pablo Castejon, Eva Onaindia, and Jeremy Frank. Robust plan execution in multi-agent environments. In 26th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), pages 384–391, 2014.
- Cesar Guzman-Alvarez, Pablo Castejon, Eva Onaindia, and Jeremy Frank. Multi-agent reactive planning for solving plan failures. In Hybrid Artificial Intelligent Systems - 8th International Conference, HAIS 2013. Volume 8073 of Lecture Notes in Computer Science, pages 530–539. Springer, 2013.
- Thomas Reinbacher, Cesar Guzman. Template-Based Synthesis of Plan Execution Monitors. In Hybrid Artificial Intelligent Systems - 8th International Conference, HAIS 2013. Volume 8073 of Lecture Notes in Computer Science, pages 451–461. Springer, 2013.
- Cesar Guzman, Vidal Alcazar, David Prior, Eva Onaindia, Daniel Borrajo, Juan Fdez-Olivares, and Ezequiel Quintero. Pelea: a domain-independent architecture for planning, execution and learning. In ICAPS 6th Scheduling and Planning Applications woRKshop (SPARK), pages 38–45, 2012.
- Cesar Guzman-Alvarez, Vidal Alcazar, David Prior, Eva Onaindia, Daniel Borrajo, Juan Fdez-Olivares. Building a Domain-Independent Architecture for Planning, Learning and Execution (PELEA). 21th International Conference on Automated Planning and Scheduling (ICAPS) - Systems Demo. pages 27-30, Freiburg (Germany), 2011
- Ezequiel Quintero, Vidal Alcazar, Daniel Borrajo, Juan Fdez-Olivares, Fernando Fernandez, Angel Garcia-Olaya, Cesar Guzman-Alvarez, Eva Onaindia, David Prior. Autonomous Mobile Robot Control and Learning with PELEA Architecture. AAAI-11 Workshop on Automated Action Planning for Autonomous Mobile Robots (PAMR). pages 51-56, San francisco (USA), 2011.
- Antonio Garrido, Cesar Guzman, and Eva Onaindia. Anytime plan-adaptation for continuous planning. In 28th Workshop of the UK Planning and Scheduling Special Interest Group (PlanSIG'10), Brescia (Italia), 2010.
- PELEA: Planning, Learning and Execution Architecture. Vidal Alcazar, Cesar Guzman-Alvarez, David Prior, Daniel Borrajo, Luis Castillo, Eva Onaindia. In 28th Workshop of the UK Planning and Scheduling Special Interest Group (PlanSIG’10), Brescia (Italia), 2010.