{"product_id":"multiagentbased-simulation-xxv-9783031880162","title":"MultiAgentBased Simulation XXV","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp class=\"heading1\" style=\"mso-list: none; tab-stops: 36.0pt;\"\u003e\u003cstrong\u003e\u003cspan lang=\"EN-US\"\u003e.- MABS Methodology and Tools.\u003c\/span\u003e\u003c\/strong\u003e\u003c\/p\u003e\u003cp class=\"heading1\" style=\"mso-list: none; tab-stops: 36.0pt;\"\u003e\u003cspan lang=\"EN-US\"\u003e\u003cspan lang=\"EN-US\" style=\"font-size: 10.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;\"\u003e.- Creating a Serious Game on top of an Agent-Based Simulation, an applied case to crisis management and population evacuation.\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\u003cp class=\"heading1\" style=\"mso-list: none; tab-stops: 36.0pt;\"\u003e\u003cspan lang=\"EN-US\"\u003e\u003cspan lang=\"EN-US\" style=\"font-size: 10.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;\"\u003e.- GENSIMO — A Generic Framework for Modelling Social Insurance Systems.\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\u003cp class=\"heading1\" style=\"mso-list: none; tab-stops: 36.0pt;\"\u003e\u003cspan lang=\"EN-US\"\u003e\u003cspan lang=\"EN-US\" style=\"font-size: 10.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;\"\u003e.- Are Low Emission Zones Effective in Reducing Emissions and Ambient Air Pollution?.\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\u003cp class=\"heading1\" style=\"mso-list: none; tab-stops: 36.0pt;\"\u003e\u003cstrong\u003e\u003cspan lang=\"EN-US\"\u003e\u003cspan lang=\"EN-US\" style=\"font-size: 10.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;\"\u003e.- \u003c\/span\u003eMABS Education.\u003c\/span\u003e\u003c\/strong\u003e\u003c\/p\u003e\u003cp class=\"heading1\" style=\"mso-list: none; tab-stops: 36.0pt;\"\u003e\u003cspan lang=\"EN-US\"\u003e\u003cspan lang=\"EN-US\" style=\"font-size: 10.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;\"\u003e.- Teaching Agent-based Modeling for Simulating Social Systems – A Research-based Learning Approach.\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\u003cp class=\"heading1\" style=\"mso-list: none; tab-stops: 36.0pt;\"\u003e\u003cstrong\u003e\u003cspan lang=\"EN-US\"\u003e\u003cspan lang=\"EN-US\" style=\"font-size: 10.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;\"\u003e.- \u003c\/span\u003eMABS Applications.\u003c\/span\u003e\u003c\/strong\u003e\u003c\/p\u003e\u003cp class=\"heading1\" style=\"mso-list: none; tab-stops: 36.0pt;\"\u003e\u003cspan lang=\"EN-US\"\u003e\u003cspan lang=\"EN-US\" style=\"font-size: 10.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;\"\u003e.- KEMASS: Knowledge-Enhanced Multi-Agent simulation for energy Scheduling Support.\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\u003cp class=\"heading1\" style=\"mso-list: none; tab-stops: 36.0pt;\"\u003e\u003cspan lang=\"EN-US\"\u003e\u003cspan lang=\"EN-US\" style=\"font-size: 10.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;\"\u003e.- Inverse Generative Approach for Identifying Agent-Based Models from Stochastic Primitives.\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\u003cp class=\"heading1\" style=\"mso-list: none; tab-stops: 36.0pt;\"\u003e\u003cspan lang=\"EN-US\"\u003e\u003cspan lang=\"EN-US\" style=\"font-size: 10.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;\"\u003e.- Inferring pedestrian decision-making through inverse reinforcement learning.\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e","brand":"Springer","offers":[{"title":"Default Title","offer_id":53195465458007,"sku":"9783031880162","price":44.99,"currency_code":"GBP","in_stock":true}],"url":"https:\/\/bookcurl.com\/products\/multiagentbased-simulation-xxv-9783031880162","provider":"Book Curl","version":"1.0","type":"link"}