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008			230116s2022 sz | s |||| 0|eng d
020			_a9783030860691
024	7		_a10.1007/978-3-030-86069-1 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTJ213 _b2022 EB
100	1		_aRussell, David W. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686013
245	1	4	_aThe BOXES Methodology : _bBlack Box Control of Ill-defined Systems _cby David W. Russell
250			_a2nd edition 2022
264		1	_aCham _bSpringer International Publishing _c2022
300			_a1 recurso en línea (XXII, 277 páginas) _b141 ilustraciones, 15 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
505	0		_aIntroduction -- Part I: Learning and Artificial Intelligence (AI) -- The Game Metaphor -- Introduction to BOXES -- Dynamic control as a game -- Part II: The Trolley and Pole -- Control of a simulated inverted pendulum using the BOXES method -- The Liverpool experiment -- Solving the auto-start dilemma -- Part III: Other BOXES applications -- Continuous system control -- Other on/off control case studies -- Two non-linear applications -- Part IV: Improving the Algorithm -- Accelerated learning -- Two advising paradigms -- Evolutionary studies research -- Part V: Further Thoughts -- Detecting and handling jitter -- Fully trained cells -- Solving the system aging paradox -- Part VI: Conclusion.
520			_aThis book focuses on how the BOXES Methodology, which is based on the work of Donald Michie, is applied to ill-defined real-time control systems with minimal a priori knowledge of the system. The method is applied to a variety of systems including the familiar pole and cart. This second edition includes a new section that covers some further observations and thoughts, problems, and evolutionary extensions that the reader will find useful in their own implementation of the method. This second edition includes a new section on how to handle jittering about a system boundary which in turn causes replicated run times to become part of the learning mechanism. It also addresses the aging of data values using a forgetfulness factor that causes wrong values of merit to be calculated. Another question that is addressed is "Should a BOXES cell ever be considered fully trained and, if so, excluded from further dynamic updates". Finally, it expands on how system boundaries may be shifted using data from many runs using an evolutionary paradigm.
988			_aSpringer_Robotics_2022
650		7	_2embne _9405125 _aControl automático
650		7	_2embne _9166090 _aAprendizaje automático
776	0	8	_iPrinted edition: _z9783030860684
776	0	8	_iPrinted edition: _z9783030860707
776	0	8	_iPrinted edition: _z9783030860714
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-86069-1 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b01/2023 _dz _eIG _zSI