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Learning to solve sequential decision-making tasks is difficult. Humans take years exploring the environment essentially in a random way until they are able to reason, solve difficult tasks, and collaborate with other humans towards a common goal. Artificial Intelligent agents are like humans in this aspect. Reinforcement Learning (RL) is a well-known technique to train autonomous agents through interactions with the environment. Unfortunately, the learning process has a high sample complexity to infer an effective actuation policy, especially when multiple agents are simultaneously actuating in the environment. However, previous knowledge can be leveraged to accelerate learning and enable s...
Learning to solve sequential decision-making tasks is difficult. Humans take years exploring the environment essentially in a random way until they are able to reason, solve difficult tasks, and collaborate with other humans towards a common goal. Artificial Intelligent agents are like humans in this aspect. Reinforcement Learning (RL) is a well-known technique to train autonomous agents through interactions with the environment. Unfortunately, the learning process has a high sample complexity to infer an effective actuation policy, especially when multiple agents are simultaneously actuating in the environment. However, previous knowledge can be leveraged to accelerate learning and enable s...
This book constitutes the proceedings of the 15th International Conference on Computational Processing of the Portuguese Language, PROPOR 2021, held in Fortaleza, Brazil, in March 2021. The 36 full papers presented together with 4 short papers were carefully reviewed and selected from 88 submissions. They are grouped in topical sections on speech processing; resources and evaluation; natural language processing applications; semantics; natural language processing tasks; and multilinguality.
IBERAMIA is the international conference series of the Ibero-American Art- cialIntelligencecommunitythathasbeenmeetingeverytwoyearssincethe1988 meeting in Barcelona. The conference is supported by the main Ibero-American societies of AI and provides researchers from Portugal, Spain, and Latin Am- ica the opportunity to meet with AI researchers from all over the world. Since 1998, IBERAMIA has been a widely recognized international conference, with its papers written and presented in English, and its proceedings published by Springer in the LNAI series. This volume contains the papers accepted for presentation at Iberamia 2008, held in Lisbon, Portugal in October 2008. For this conference, 14...
This volume constitutes selected papers presented at the First International Conference on Engineering Software for Modern Challenges, ESMoC 2021, held in Johor, Malaysia, in October 20-21, 2021. The 17 papers presented were thoroughly reviewed and selected from the 167 submissions. They are organized in the topical sections on software engineering; intelligent systems; software quality.
Reinforcement learning is a powerful tool in artificial intelligence in which virtual or physical agents learn to optimize their decision making to achieve long-term goals. In some cases, this machine learning approach can save programmers time, outperform existing controllers, reach super-human performance, and continually adapt to changing conditions. This book argues that these successes show reinforcement learning can be adopted successfully in many different situations, including robot control, stock trading, supply chain optimization, and plant control. However, reinforcement learning has traditionally been limited to applications in virtual environments or simulations in which the set...
This three-volume set LNAI 6911, LNAI 6912, and LNAI 6913 constitutes the refereed proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2011, held in Athens, Greece, in September 2011. The 121 revised full papers presented together with 10 invited talks and 11 demos in the three volumes, were carefully reviewed and selected from about 600 paper submissions. The papers address all areas related to machine learning and knowledge discovery in databases as well as other innovative application domains such as supervised and unsupervised learning with some innovative contributions in fundamental issues; dimensionality reduction, distance and similarity learning, model learning and matrix/tensor analysis; graph mining, graphical models, hidden markov models, kernel methods, active and ensemble learning, semi-supervised and transductive learning, mining sparse representations, model learning, inductive logic programming, and statistical learning. a significant part of the papers covers novel and timely applications of data mining and machine learning in industrial domains.
Researchers have obtained robots that display an amazing slew of behaviors and perform a multitude of tasks, including perception of environment, negotiating rough terrain, and pushing boxes. This volume offers a wide spectrum of sample works developed in leading research throughout the world about evolutionary mobile robotics and demonstrates the success of the technique in evolving efficient and capable mobile robots.
This book constitutes the refereed proceedings of the 4th International Conference on Simulation, Modeling, and Programming for Autonomous Robots, SIMPAR 2014, held in Bergamo, Italy, in October 2014. The 49 revised full papers presented were carefully reviewed and selected from 62 submissions. The papers are organized in topical sections on simulation, modeling, programming, architectures, methods and tools, and systems and applications.
This book includes the post-conference proceedings of the 20th RoboCup International Symposium, held in Leipzig, Germany, in July 2016. In addition to the 38 contributions to the symposium, selected from 63 submissions, the book also contains 15 champion papers of teams winning individual leagues of the RoboCup 2016 competition, the Amazon Picking Challenge, and the Harting Open Source Award. The papers present current research in the fields of robotics and artificial intelligence with a special focus to robot hardware and software, environment perception, action planning and control, robot learning, multi-robot systems, and human-robot interaction.