{"_buckets": {"deposit": "2483380a-bfbd-4b4b-8b3b-00e64da6ef63"}, "_deposit": {"id": "2005222", "owners": [1], "pid": {"revision_id": 0, "type": "depid", "value": "2005222"}, "status": "published"}, "_oai": {"id": "oai:u-ryukyu.repo.nii.ac.jp:02005222", "sets": ["1642837875711", "1642838406845"]}, "author_link": [], "item_1617186331708": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "\u30de\u30eb\u30c1\u30a8\u30fc\u30b8\u30a7\u30f3\u30c8\u7cfb\u306b\u304a\u3051\u308b\u7af6\u5408\u5171\u9032\u5316\u578b\u5b66\u7fd2\u306e\u6027\u80fd\u8a55\u4fa1", "subitem_1551255648112": "ja"}, {"subitem_1551255647225": "The performance evaluation of competitive co-evolution in multi-agent system.", "subitem_1551255648112": "en"}]}, "item_1617186419668": {"attribute_name": "Creator", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "\u7389\u57ce, \u6e05\u653f", "creatorNameLang": "ja"}]}, {"creatorNames": [{"creatorName": "\u7389\u57ce, \u6589", "creatorNameLang": "ja"}]}, {"creatorNames": [{"creatorName": "\u5c71\u7530, \u5b5d\u6cbb", "creatorNameLang": "ja"}]}, {"creatorNames": [{"creatorName": "\u9060\u85e4, \u8061\u5fd7", "creatorNameLang": "ja"}]}, {"creatorNames": [{"creatorName": "Tamashiro, Kiyomasa", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "Tamaki, Tadashi", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "Yamada, Koji", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "Endo, Satoshi", "creatorNameLang": "en"}]}]}, "item_1617186476635": {"attribute_name": "Access Rights", "attribute_value_mlt": [{"subitem_1522299639480": "open access", "subitem_1600958577026": "http://purl.org/coar/access_right/c_abf2"}]}, "item_1617186609386": {"attribute_name": "Subject", "attribute_value_mlt": [{"subitem_1522299896455": "en", "subitem_1522300014469": "Other", "subitem_1523261968819": "Reinforcement learning"}, {"subitem_1522299896455": "en", "subitem_1522300014469": "Other", "subitem_1523261968819": "Genetic algorithm"}, {"subitem_1522299896455": "en", "subitem_1522300014469": "Other", "subitem_1523261968819": "competitive co-evolution"}]}, "item_1617186626617": {"attribute_name": "Description", "attribute_value_mlt": [{"subitem_description": "One of the important issues in intelligent systems and robotics is to develop an efficient method to control multi-agent system. In order to work multi-agent system well as problem solver, it\u0027s so significant to create cooperative behaviors among the agents. In the multi-agent system, the behaviors of cooperation emerged as the results of suitable role learning by each agent. In this paper, we evaluate reinforcement learning, genetic algorithm and competitive co-evolution algorithm from the viewpoint of adaptability to different environment as the learning method of multi-agent system, and discuss the property of each technique.", "subitem_description_type": "Other"}, {"subitem_description": "\u7d00\u8981\u8ad6\u6587", "subitem_description_type": "Other"}]}, "item_1617186643794": {"attribute_name": "Publisher", "attribute_value_mlt": [{"subitem_1522300295150": "ja", "subitem_1522300316516": "\u7409\u7403\u5927\u5b66\u5de5\u5b66\u90e8"}]}, "item_1617186702042": {"attribute_name": "Language", "attribute_value_mlt": [{"subitem_1551255818386": "jpn"}]}, "item_1617186783814": {"attribute_name": "Identifier", "attribute_value_mlt": [{"subitem_identifier_type": "HDL", "subitem_identifier_uri": "http://hdl.handle.net/20.500.12000/14710"}]}, "item_1617186920753": {"attribute_name": "Source Identifier", "attribute_value_mlt": [{"subitem_1522646500366": "ISSN", "subitem_1522646572813": "0389-102X"}, {"subitem_1522646500366": "NCID", "subitem_1522646572813": "AN0025048X"}]}, "item_1617186941041": {"attribute_name": "Source Title", "attribute_value_mlt": [{"subitem_1522650068558": "ja", "subitem_1522650091861": "\u7409\u7403\u5927\u5b66\u5de5\u5b66\u90e8\u7d00\u8981"}]}, "item_1617187056579": {"attribute_name": "Bibliographic Information", "attribute_value_mlt": [{"bibliographicIssueNumber": "58", "bibliographicPageEnd": "149", "bibliographicPageStart": "143"}]}, "item_1617258105262": {"attribute_name": "Resource Type", "attribute_value_mlt": [{"resourcetype": "departmental bulletin paper", "resourceuri": "http://purl.org/coar/resource_type/c_6501"}]}, "item_1617265215918": {"attribute_name": "Version Type", "attribute_value_mlt": [{"subitem_1522305645492": "VoR", "subitem_1600292170262": "http://purl.org/coar/version/c_970fb48d4fbd8a85"}]}, "item_1617605131499": {"attribute_name": "File", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "download_preview_message": "", "file_order": 0, "filename": "No58p143.pdf", "future_date_message": "", "is_thumbnail": false, "mimetype": "", "size": 0, "url": {"objectType": "fulltext", "url": "https://u-ryukyu.repo.nii.ac.jp/record/2005222/files/No58p143.pdf"}, "version_id": "1a1eaf82-3e3e-478b-abc9-5ab1d1e9bd6a"}]}, "item_title": "\u30de\u30eb\u30c1\u30a8\u30fc\u30b8\u30a7\u30f3\u30c8\u7cfb\u306b\u304a\u3051\u308b\u7af6\u5408\u5171\u9032\u5316\u578b\u5b66\u7fd2\u306e\u6027\u80fd\u8a55\u4fa1", "item_type_id": "15", "owner": "1", "path": ["1642837875711", "1642838406845"], "permalink_uri": "http://hdl.handle.net/20.500.12000/14710", "pubdate": {"attribute_name": "PubDate", "attribute_value": "2010-01-13"}, "publish_date": "2010-01-13", "publish_status": "0", "recid": "2005222", "relation": {}, "relation_version_is_last": true, "title": ["\u30de\u30eb\u30c1\u30a8\u30fc\u30b8\u30a7\u30f3\u30c8\u7cfb\u306b\u304a\u3051\u308b\u7af6\u5408\u5171\u9032\u5316\u578b\u5b66\u7fd2\u306e\u6027\u80fd\u8a55\u4fa1"], "weko_shared_id": -1}
マルチエージェント系における競合共進化型学習の性能評価
http://hdl.handle.net/20.500.12000/14710
http://hdl.handle.net/20.500.12000/14710