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This book constitutes the refereed proceedings of the 20th Australian Joint Conference on Artificial Intelligence, AI 2007, held in Gold Coast, Australia, in December 2007.The 58 revised full papers and 40 revised short papers presented together with the extended abstracts of three invited speeches were carefully reviewed and selected from 194 submissions. The papers are organized in topical sections on a broad range of subjects.
This book constitutes the refereed proceedings of the 43rd German Conference on Artificial Intelligence, KI 2020, held in Bamberg, Germany, in September 2020. The 16 full and 12 short papers presented together with 6 extended abstracts in this volume were carefully reviewed and selected from 62 submissions. As well-established annual conference series KI is dedicated to research on theory and applications across all methods and topic areas of AI research. KI 2020 had a special focus on human-centered AI with highlights on AI and education and explainable machine learning. Due to the Corona pandemic KI 2020 was held as a virtual event.
Examines the creation of software programs displaying broad, deep, human-style general intelligence. This work features papers presented at the 2006 AGIRI (Artificial General Intelligence Research Institute) workshop, which illustrates that it is a fit and proper subject for serious science and engineering exploration.
We are pleased to present this LNCS volume, the Proceedings of the 22nd A- tralasianJointConferenceonArti?cialIntelligence(AI2009),heldinMelbourne, Australia, December 1–4,2009.This long established annual regionalconference is a forum both for the presentation of researchadvances in arti?cial intelligence and for scienti?c interchange amongst researchers and practitioners in the ?eld of arti?cial intelligence. Conference attendees were also able to enjoy AI 2009 being co-located with the Australasian Data Mining Conference (AusDM 2009) and the 4th Australian Conference on Arti?cial Life (ACAL 2009). This year AI 2009 received 174 submissions, from authors of 30 di?erent countries. After an extensive peer review process where each submitted paper was rigorously reviewed by at least 2 (and in most cases 3) independent revi- ers, the best 68 papers were selected by the senior Program Committee for oral presentation at the conference and included in this volume, resulting in an - ceptance rate of 39%. The papers included in this volume cover a wide range of topics in arti?cial intelligence: from machine learning to natural language s- tems, from knowledge representation to soft computing, from theoretical issues to real-world applications. AI 2009 also included 11 tutorials, available through the First Australian Computational Intelligence Summer School (ACISS 2009). These tutorials – some introductory, some advanced – covered a wide range of research topics within arti?cial intelligence, including data mining, games, evolutionary c- putation, swarm optimization, intelligent agents, Bayesian and belief networks.
This book constitutes the refereed proceedings of the 23rd Australasian Joint Conference on Artificial Intelligence, AI 2010, held in Adelaide, Australia, in December 2010. The 52 revised full papers presented were carefully reviewed and selected from 112 submissions. The papers are organized in topical sections on knowledge representation and reasoning; data mining and knowledge discovery; machine learning; statistical learning; evolutionary computation; particle swarm optimization; intelligent agent; search and planning; natural language processing; and AI applications.
This book constitutes the refereed proceedings of the 21th Australasian Joint Conference on Artificial Intelligence, AI 2008, held in Auckland, New Zealand, in December 2008. The 42 revised full papers and 21 revised short papers presented together with 1 invited lecture were carefully reviewed and selected from 143 submissions. The papers are organized in topical sections on knowledge representation, constraints, planning, grammar and language processing, statistical learning, machine learning, data mining, knowledge discovery, soft computing, vision and image processing, and AI applications.
This book constitutes the thoroughly refereed proceedings of the 30th Annual German Conference on Artificial Intelligence, KI 2007, held in Osnabrück, Germany, September 2007. The papers are organized in topical sections on cognition and emotion, semantic Web, analogy, natural language, reasoning, ontologies, spatio-temporal reasoning, machine learning, spatial reasoning, robot learning, classical AI problems, and agents.
This book constitutes the refereed proceedings of the 14th International Conference of the Italian Association for Artificial Intelligence, A*IA 2015, held in Ferrara, Italy, in September 2015. The 35 full papers presented were carefully reviewed and selected from 44 submissions. The papers are organized in topical sections on swarm intelligence and genetic algorithms; computer vision; multi-agents systems; knowledge representation and reasoning; machine learning; semantic Web; natural language; and scheduling, planning and robotics.
This book constitutes the refereed proceedings of the 20th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2007, held in Montreal, Canada, in May 2007. The 46 revised full papers cover agents, bioinformatics, classification, constraint satisfaction, data mining, knowledge representation and reasoning, learning, natural language, and planning.
A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.