Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Martin Takac"'
Publikováno v:
IEEE Access, Vol 11, Pp 87958-87969 (2023)
We present a novel end-to-end framework for solving the Vehicle Routing Problem with stochastic demands (VRPSD) using Reinforcement Learning (RL). Our formulation incorporates the correlation between stochastic demands through other observable stocha
Externí odkaz:
https://doaj.org/article/8106d37416784508906865d6f0a2a522
Autor:
Martin Takac, Jan Sefranek
Publikováno v:
Interdisciplinary Description of Complex Systems, Vol 10, Iss 3, Pp 248-269 (2012)
In this article we are aiming to build cognitive semantics over a first person perspective. Our goal is to specify meanings connected to cognitive agents, rooted in their experience and separable from language, covering a wide spectrum of cognitions
Externí odkaz:
https://doaj.org/article/e9a08fb7075a4797aa3768eb0c7a12bd
Autor:
Mark Sagar, Annette M. E. Henderson, Martin Takac, Samara Morrison, Alistair Knott, Alecia Moser, Wan-Ting Yeh, Nathan Pages, Khurram Jawed
Publikováno v:
Journal of the Royal Society of New Zealand. 53:148-168
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2bbafcf135bb750f0ff8eae0f6962bde
https://doi.org/10.1080/03036758.2022.2098781
https://doi.org/10.1080/03036758.2022.2098781
Publikováno v:
AI and Ethics. 2:115-128
As AI advances, models of simulated humans are becoming increasingly realistic. A new debate has arisen about the ethics of interacting with these realistic agents—and in particular, whether any harms arise from ‘mistreatment’ of such agents. I
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2dbd7b505106d99736adef6b3dcc8f78
https://doi.org/10.1007/s43681-021-00076-x
https://doi.org/10.1007/s43681-021-00076-x
Autor:
Alistair Knott, Martin Takac
Publikováno v:
Topics in Cognitive Science. 13:187-205
The unifying theme for the papers in this volume is that event-predictive representations play an important role in cognitive processes, and they are a particularly fruitful object of study for cognitive scientists. In this paper, we present our own
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1a97cdaf7fc0b25028afe0ac2d3f5efe
https://doi.org/10.1111/tops.12497
https://doi.org/10.1111/tops.12497
Autor:
Nathan Pages, Jonathan Conder, Martin Takac, Alecia Moser, Khurram Jawed, Sam Morrison, Mark Sagar, Annette M. E. Henderson, Alireza Nejati, Wan-Ting Yeh, Alistair Knott
Publikováno v:
ICDL
While most modelling efforts focus on particular components of the infant cognitive system studied in isolation, we have developed a model of a ‘whole baby’: a graphical simulation of a baby, whose behaviour is produced by a multi-component brain
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::391281119961fe3798051d503e88553a
https://doi.org/10.1109/icdl49984.2021.9515612
https://doi.org/10.1109/icdl49984.2021.9515612
Autor:
Mark Sagar, Alecia Moser, Annette M. E. Henderson, Sam Morrison, Nathan Pages, Alireza Nejati, Wan-Ting Yeh, Jonathan Conder, Alistair Knott, Khurram Jawed, Martin Takac
Publikováno v:
IEEE Transactions on Cognitive and Developmental Systems. :1-1
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ed6fd56d2c162977dd23b2a731769cf1
https://doi.org/10.1109/tcds.2022.3188152
https://doi.org/10.1109/tcds.2022.3188152
Autor:
Piotr M. Patrzyk, Martin Takac
Publikováno v:
Adaptive Behavior. 25:83-95
People often cooperate and obey norms in situations where it is clear they cannot be caught and punished. Such behavior does not serve their self-interest, as they are foregoing opportunities to exploit others without any negative consequences. Hence
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e9c542b32f0a9dd8acb22e99bd97c3c8
https://doi.org/10.1177/1059712317693889
https://doi.org/10.1177/1059712317693889
Publikováno v:
Artificial Neural Networks and Machine Learning – ICANN 2020 ISBN: 9783030616083
ICANN (1)
ICANN (1)
In this paper we present a connectionist architecture called C-block combining several powerful and cognitively relevant features. It can learn sequential dependencies in incoming data and predict probability distributions over possible next inputs,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::81de6e6298e10cca832f5cf221858c0b
https://doi.org/10.1007/978-3-030-61609-0_53
https://doi.org/10.1007/978-3-030-61609-0_53
