{"id":24332679,"url":"https://github.com/silviatulli/suboptimax","last_synced_at":"2025-08-17T01:06:43.886Z","repository":{"id":84541961,"uuid":"306632142","full_name":"Silviatulli/suboptimax","owner":"Silviatulli","description":"minmax planner for suboptimal explanations - Explainable Agency by Revealing Suboptimality in CHRI Learning Scenarios","archived":false,"fork":false,"pushed_at":"2021-06-02T16:03:46.000Z","size":34,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-05-01T12:05:21.911Z","etag":null,"topics":["catkin","chri-learning-scenarios","explainable-ai","minmax-algorithm","pynaoqi-sdk","ros-melodic","sequential-decision-making-problems"],"latest_commit_sha":null,"homepage":"","language":"Python","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/Silviatulli.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,"zenodo":null}},"created_at":"2020-10-23T12:37:12.000Z","updated_at":"2021-06-02T16:05:59.000Z","dependencies_parsed_at":"2023-03-12T23:24:41.912Z","dependency_job_id":null,"html_url":"https://github.com/Silviatulli/suboptimax","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Silviatulli/suboptimax","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Silviatulli%2Fsuboptimax","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Silviatulli%2Fsuboptimax/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Silviatulli%2Fsuboptimax/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Silviatulli%2Fsuboptimax/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Silviatulli","download_url":"https://codeload.github.com/Silviatulli/suboptimax/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Silviatulli%2Fsuboptimax/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":270792174,"owners_count":24646022,"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","status":"online","status_checked_at":"2025-08-16T02:00:11.002Z","response_time":91,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":["catkin","chri-learning-scenarios","explainable-ai","minmax-algorithm","pynaoqi-sdk","ros-melodic","sequential-decision-making-problems"],"created_at":"2025-01-18T02:45:46.056Z","updated_at":"2025-08-17T01:06:43.868Z","avatar_url":"https://github.com/Silviatulli.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"## Explainable Agency by Revealing Suboptimalityin Child-Robot Learning Scenarios\nRevealing the internal workings of a robot can help a human better understand the robot's behaviors. How to reveal such workings, e.g., via explanation generation, remains a significant challenge. This gets even more complex when these explanations are targeted towards children.\nTherefore, we propose a search-based approach to generate contrastive explanations using optimal and sub-optimal plans and implement it in a scenario for children. In the application scenario, the child and the robot learn together how to play a zero-sum game that requires logical and mathematical thinking.\nWe report results around our explanation generation system that was successfully deployed among seven-year-old children. Our results show trends that the generated explanations were able to positively affect the children's perceived difficulty in learning the zero-sum game.\n\nFor additional details about the research work you can check out our paper: [Explainable Agency by Revealing Suboptimalityin Child-Robot Learning Scenarios](https://link.springer.com/chapter/10.1007/978-3-030-62056-1_3)\n\n## Test\nTo run the code:\n- open a terminal and launch: $ roscore\n- open a second terminal into your repository folder and launch minmax.launch: $ roslaunch minmax.launch\n\n## Config\n- **Install [ROS melodic](http://wiki.ros.org/melodic) and [catkin](https://wiki.ros.org/catkin#Installing_catkin)**\n\n- **Clone the repository**\n   - $ git clone https://github.com/Silviatulli/suboptimax.git\n\n- **Make the python files executable** \n Run the following command for each script:\n - $ chmod +x filename.py\n\n- **Build a catkin workspace and source the setup file**\n  - $ cd ~/catkin_ws\n  - $ catkin_make\n\n- **Add the workspace to the ROS environment**\n  - $. ~/catkin_ws/devel/setup.bash\n\n- **Make sure that the CMakeLists.txt file is configured properly** \n   - All the services and the dependencies should be as follows:\n      - find_package (catkin REQUIRED COMPONENTS roscpp rospy std_msgs message_generation message_runtime )\n      - add_service_files (FILES Decision.srv GameState.srv Plan.srv RobotExplanation.srv RobotTalk.srv )\n\n- **Make it work with the Robot**\n   - If you work with the NAO Robot uncomment the line 7, from 41 to 65 and 85 (self.robot_communication.say(self.explanation_text)) in the file robot_manager.py. \n   - Create a folder sdk that contains the pynaoqi sdk required and modify your bashrc ($gedit ~/.bashrc) to indicate the python and library paths as follows:\n      - export PYTHONPATH=$PYTHONPATH:~/sdk/pynaoqi-python2.7-2.1.2.17-linux64\n      - export LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:/home/\u003cyour_pc_name\u003e/sdk/pynaoqi-python2.7-2.1.2.17-linux64\n      - you can download the pynaoqi sdk following this [guide](http://wiki.ros.org/nao/Tutorials/Installation)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsilviatulli%2Fsuboptimax","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsilviatulli%2Fsuboptimax","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsilviatulli%2Fsuboptimax/lists"}