{"id":18896618,"url":"https://github.com/cguz/planning-reactive-planner","last_synced_at":"2025-10-03T23:53:38.957Z","repository":{"id":154811324,"uuid":"195390982","full_name":"cguz/planning-reactive-planner","owner":"cguz","description":"Reactive plan execution in multi-agent environments","archived":false,"fork":false,"pushed_at":"2021-03-20T12:45:36.000Z","size":73591,"stargazers_count":3,"open_issues_count":0,"forks_count":1,"subscribers_count":0,"default_branch":"master","last_synced_at":"2024-12-31T08:14:48.535Z","etag":null,"topics":["agent","multiagent","prediction","reactive-planner"],"latest_commit_sha":null,"homepage":"","language":"Java","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/cguz.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2019-07-05T10:32:26.000Z","updated_at":"2023-07-23T18:34:55.000Z","dependencies_parsed_at":null,"dependency_job_id":"82752769-eb4d-4428-9347-1288525c5737","html_url":"https://github.com/cguz/planning-reactive-planner","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cguz%2Fplanning-reactive-planner","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cguz%2Fplanning-reactive-planner/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cguz%2Fplanning-reactive-planner/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cguz%2Fplanning-reactive-planner/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/cguz","download_url":"https://codeload.github.com/cguz/planning-reactive-planner/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":239876800,"owners_count":19711956,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["agent","multiagent","prediction","reactive-planner"],"created_at":"2024-11-08T08:34:48.789Z","updated_at":"2025-10-03T23:53:33.924Z","avatar_url":"https://github.com/cguz.png","language":"Java","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Reactive plan execution in multi-agent environments\n\n\n\u003cdiv align=center\u003e\n  \u003ca href=\"https://www.upv.es\"\u003e\u003cimg src=\"https://github.com/cguz/planning-reactive-planner/raw/master/image/upv.png\" alt=\"UPV\" title=\"UPV\" hspace=\"30\" height=\"96px\" /\u003e\u003c/a\u003e\n  \u003ca href=\"https://www.nasa.org\"\u003e\u003cimg src=\"https://raw.githubusercontent.com/cguz/planning-reactive-planner/de2d965beed33632b2c2a5f8ffb9bfd15a89fee4/image/nasa.svg\" alt=\"NASA\" title=\"NASA\" hspace=\"30\" height=\"96px\" /\u003e\u003c/a\u003e\n  \u003cimg src=\"https://github.com/cguz/planning-reactive-planner/raw/master/image/GobSpain.png\" alt=\"Gobierno de españa\" title=\"Gobierno de españa\" hspace=\"30\" height=\"96px\" /\u003e\n\u003c/div\u003e\n\n\n\nAuthor: Guzmán-Álvarez, César A. [@cguz](https://github.com/cguz)\n\nAdvisor: Eva Onaindia\n\nCollaborator: Jeremy Frank\n\nThe 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](https://riunet.upv.es/bitstream/handle/10251/120457/G%c3%bazman%20-%20Reactive%20plan%20execution%20in%20multi-agent%20environments.pdf?sequence=4\u0026isAllowed=y).\n\nThe 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. \n\nThe 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.\n\n## Abstract \n\nWe 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.\n\nThe 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.\n\n## Architecture\n\n![image](https://user-images.githubusercontent.com/15159632/111842903-7a4ffd80-8900-11eb-8bcf-a55584bd9297.png)\n\n## Source code\n\n[![Java](https://img.shields.io/badge/Java-8-red)](https://www.java.org/)\n\nThe folder \"src\" contains the code of the reactive planner in Java. It is executable only for a single agent. \n\nPlease, if something fails or is missing email me : cguzman at cguz dot org.\n\n## Publications\n\nThe whole work of this thesis have led to a series of publications, which we referenced throughout the memory. Of these, the\nfollowing stand out:\n\n* 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.\n* 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.\n* 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.\n* 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.\n* 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.\n* 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\n* 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.\n* 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.\n* 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.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcguz%2Fplanning-reactive-planner","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcguz%2Fplanning-reactive-planner","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcguz%2Fplanning-reactive-planner/lists"}