{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T01:35:01Z","timestamp":1742952901610,"version":"3.40.3"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031167690"},{"type":"electronic","value":"9783031167706"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-16770-6_10","type":"book-chapter","created":{"date-parts":[[2022,9,8]],"date-time":"2022-09-08T22:03:22Z","timestamp":1662674602000},"page":"115-126","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Adapting to\u00a0Environment Changes Through Neuromodulation of\u00a0Reinforcement Learning"],"prefix":"10.1007","author":[{"given":"Jinwei","family":"Xing","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinyun","family":"Zou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Praveen K.","family":"Pilly","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicholas A.","family":"Ketz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jeffrey L.","family":"Krichmar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,9,9]]},"reference":[{"issue":"7587","key":"10_CR1","doi-asserted-by":"publisher","first-page":"484","DOI":"10.1038\/nature16961","volume":"529","author":"D Silver","year":"2016","unstructured":"Silver, D., et al.: Mastering the game of Go with deep neural networks and tree search. Nature 529(7587), 484\u2013489 (2016)","journal-title":"Nature"},{"issue":"7540","key":"10_CR2","doi-asserted-by":"publisher","first-page":"529","DOI":"10.1038\/nature14236","volume":"518","author":"V Mnih","year":"2015","unstructured":"Mnih, V., et al.: Human-level control through deep reinforcement learning. Nature 518(7540), 529\u2013533 (2015)","journal-title":"Nature"},{"key":"10_CR3","unstructured":"Akkaya, I., et al.: Solving Rubik\u2019s cube with a robot hand. arXiv preprint arXiv:1910.07113 (2019)"},{"key":"10_CR4","unstructured":"Lillicrap, T.P., et al.: Continuous control with deep reinforcement learning. arXiv preprint arXiv:1509.02971 (2015)"},{"issue":"2","key":"10_CR5","doi-asserted-by":"publisher","first-page":"1312","DOI":"10.1109\/LRA.2021.3057023","volume":"6","author":"G Kahn","year":"2021","unstructured":"Kahn, G., Abbeel, P., Levine, S.: BADGR: an autonomous self-supervised learning-based navigation system. IEEE Robot. Autom. Lett. 6(2), 1312\u20131319 (2021)","journal-title":"IEEE Robot. Autom. Lett."},{"key":"10_CR6","doi-asserted-by":"crossref","unstructured":"Xing, J., Zou, X., Krichmar, J.L.: Neuromodulated patience for robot and self-driving vehicle navigation. In: 2020 International Joint Conference on Neural Networks (IJCNN), pp. 1\u20138. IEEE, July 2020","DOI":"10.1109\/IJCNN48605.2020.9206642"},{"issue":"5","key":"10_CR7","doi-asserted-by":"publisher","first-page":"1936","DOI":"10.1523\/JNEUROSCI.16-05-01936.1996","volume":"16","author":"PR Montague","year":"1996","unstructured":"Montague, P.R., Dayan, P., Sejnowski, T.J.: A framework for mesencephalic dopamine systems based on predictive Hebbian learning. J. Neurosci. 16(5), 1936\u20131947 (1996)","journal-title":"J. Neurosci."},{"issue":"5306","key":"10_CR8","doi-asserted-by":"publisher","first-page":"1593","DOI":"10.1126\/science.275.5306.1593","volume":"275","author":"W Schultz","year":"1997","unstructured":"Schultz, W., Dayan, P., Montague, P.R.: A neural substrate of prediction and reward. Science 275(5306), 1593\u20131599 (1997)","journal-title":"Science"},{"issue":"22","key":"10_CR9","doi-asserted-by":"publisher","first-page":"5623","DOI":"10.1523\/JNEUROSCI.1309-08.2008","volume":"28","author":"TA Hare","year":"2008","unstructured":"Hare, T.A., O\u2019Doherty, J., Camerer, C.F., Schultz, W., Rangel, A.: Dissociating the role of the orbitofrontal cortex and the striatum in the computation of goal values and prediction errors. J. Neurosci. 28(22), 5623\u20135630 (2008)","journal-title":"J. Neurosci."},{"issue":"6","key":"10_CR10","doi-asserted-by":"publisher","first-page":"845","DOI":"10.1038\/nn.4287","volume":"19","author":"NF Parker","year":"2016","unstructured":"Parker, N.F., et al.: Reward and choice encoding in terminals of midbrain dopamine neurons depends on striatal target. Nat. Neurosci. 19(6), 845\u2013854 (2016)","journal-title":"Nat. Neurosci."},{"issue":"4","key":"10_CR11","doi-asserted-by":"publisher","first-page":"681","DOI":"10.1016\/j.neuron.2005.04.026","volume":"46","author":"JY Angela","year":"2005","unstructured":"Angela, J.Y., Dayan, P.: Uncertainty, neuromodulation, and attention. Neuron 46(4), 681\u2013692 (2005)","journal-title":"Neuron"},{"key":"10_CR12","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1016\/j.neunet.2020.01.031","volume":"125","author":"X Zou","year":"2020","unstructured":"Zou, X., Kolouri, S., Pilly, P.K., Krichmar, J.L.: Neuromodulated attention and goal-driven perception in uncertain domains. Neural Netw. 125, 56\u201369 (2020)","journal-title":"Neural Netw."},{"key":"10_CR13","unstructured":"Chevalier-Boisvert, M., Willems, L., Pal, S.: Minimalistic gridworld environment for OpenAI Gym. GitHub Repository (2018). https:\/\/github.com\/maximecb\/gym-minigrid"},{"key":"10_CR14","unstructured":"Fujimoto, S., Hoof, H., Meger, D.: Addressing function approximation error in actor-critic methods. In: International Conference on Machine Learning, pp. 1587\u20131596. PMLR, July 2018"},{"key":"10_CR15","unstructured":"Schulman, J., Wolski, F., Dhariwal, P., Radford, A., Klimov, O.: Proximal policy optimization algorithms. arXiv preprint arXiv:1707.06347 (2017)"},{"issue":"3","key":"10_CR16","doi-asserted-by":"publisher","first-page":"445","DOI":"10.1523\/JNEUROSCI.1956-18.2018","volume":"39","author":"SL Grella","year":"2019","unstructured":"Grella, S.L., et al.: Locus coeruleus phasic, but not tonic, activation initiates global remapping in a familiar environment. J. Neurosci. 39(3), 445\u2013455 (2019)","journal-title":"J. Neurosci."},{"issue":"11","key":"10_CR17","doi-asserted-by":"publisher","first-page":"574","DOI":"10.1016\/j.tins.2005.09.002","volume":"28","author":"S Bouret","year":"2005","unstructured":"Bouret, S., Sara, S.J.: Network reset: a simplified overarching theory of locus coeruleus noradrenaline function. Trends Neurosci. 28(11), 574\u2013582 (2005)","journal-title":"Trends Neurosci."},{"key":"10_CR18","unstructured":"Tassa, Y., et al.: Deepmind control suite. arXiv preprint arXiv:1801.00690 (2018)"}],"container-title":["Lecture Notes in Computer Science","From Animals to Animats 16"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-16770-6_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,12]],"date-time":"2022-09-12T23:06:01Z","timestamp":1663023961000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-16770-6_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031167690","9783031167706"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-16770-6_10","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"9 September 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SAB","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Simulation of Adaptive Behavior","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Cergy-Pontoise","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"France","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 September 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 September 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"sab2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Scienceconf.org","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"23","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"17","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"74% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}