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Behaviour Suite for Reinforcement Learning [article]

Ian Osband, Yotam Doron, Matteo Hessel, John Aslanides, Eren Sezener, Andre Saraiva, Katrina McKinney, Tor Lattimore, Csaba Szepesvari, Satinder Singh, Benjamin Van Roy, Richard Sutton, David Silver (+1 others)
2020 arXiv   pre-print
This paper introduces the Behaviour Suite for Reinforcement Learning, or bsuite for short. bsuite is a collection of carefully-designed experiments that investigate core capabilities of reinforcement learning  ...  Second, to study agent behaviour through their performance on these shared benchmarks.  ...  Related work The Behaviour Suite for Reinforcement Learning fits into a long history of RL benchmarks.  ... 
arXiv:1908.03568v3 fatcat:vn6qvna3wvcztplbsyb6i5nkqu

Obstacle Avoidance through Reinforcement Learning

Tony J. Prescott, John E. W. Mayhew
1991 Neural Information Processing Systems  
A method is described for generating plan-like. reflexive. obstacle avoidance behaviour in a mobile robot. The experiments reported here use a simulated vehicle with a primitive range sensor.  ...  Avoidance behaviour is encoded as a set of continuous functions of the perceptual input space.  ...  to suit the new circumstances.  ... 
dblp:conf/nips/PrescottM91 fatcat:cayohbxrtjallnile564hhay7u

EVO-RL: Evolutionary-Driven Reinforcement Learning [article]

Ahmed Hallawa, Thorsten Born, Anke Schmeink, Guido Dartmann, Arne Peine, Lukas Martin, Giovanni Iacca, A. E. Eiben, Gerd Ascheid
2020 arXiv   pre-print
In this work, we propose a novel approach for reinforcement learning driven by evolutionary computation.  ...  In addition, evo-RL facilitates learning on environments with rewardless states, which makes it more suited for real-world problems with incomplete information.  ...  of defining a reward function suited for the majority of states in that environment.  ... 
arXiv:2007.04725v2 fatcat:yhxpzgo74bfa3m2h6t5jubm6xi


Ahmad Abdullahi Abdallah, Lawal Mustafa Usman
2017 Sokoto Educational Review  
and effective learning were discussed.  ...  The paper discusses behaviour modification techniques as a mean of addressing the negative behaviour exhibited by pupils in primary schools.  ...  Some of these techniques needed to modify behaviour for effective teaching/learning in primary schools in Nigeria include: Reinforcement Reinforcements are the ways in which a desired behaviour is encouraged  ... 
doi:10.35386/ser.v17i2.37 fatcat:z7cg2exw2jfgpn6uhzsp6qryjm

Relevance of Skinner's Theory of Reinforcement on Effective School Evaluaution and Management

O. Austin Omomia, T. A. Omomia
2014 European Journal of Psychological Studies  
Skinner's theory of reinforcement emphasizes on the relevance of reward and punishment. This has impacted, to a large extent on the promotion of teaching and learning.  ...  Students' educational outcomes can be improved upon on the basis of positive reinforcements.  ...  This means positive reinforcers for favourable behaviour and negative reinforcers to discourage inappropriate behaviours. What is the impact of reinforcement behaviours on teacher's performance?  ... 
doi:10.13187/ejps.2014.6.174 fatcat:gwud6lkaevdurfe6ixa63nemii

Traffic Light Tool e‐Learning Course [to support professionals' use of Brook's sexual behaviours Traffic Light Tool to identify, understand and respond appropriately to sexual behaviours in young people], 2021. £30 per person. Available:‐light‐tool

Debra Allnock, William Baginsky
2021 Child Abuse Review  
Traffic Light Tool e-Learning Course [to support professionals' use of Brook's sexual behaviours Traffic Light Tool to identify, understand and respond appropriately to sexual behaviours in young people  ...  Available: '[The tool] aims to support professionals to be confident and proactive in identifying sexualised behaviours'  ...  The course is reinforcing and provides plenty of opportunity for application.  ... 
doi:10.1002/car.2684 fatcat:t6piukrqczbkvo6wx6yajzf4tm

Probabilistic Computation and Emotion as Self-regulation

Rickard von Haugwitz, Gordana Dodig-Crnkovic
2015 Proceedings of the 2015 European Conference on Software Architecture Workshops - ECSAW '15  
Various implications of these models are examined in the context of reinforcement learning through a review of recent research.  ...  A treatment of emotion as a means of meta-optimisation in cognitive systems is presented, drawing upon research in neuroscience and reinforcement learning.  ...  The intensity, a number in [0,1], is then used in the computation of an intrinsic reward function for a reinforcement learning agent.  ... 
doi:10.1145/2797433.2797442 dblp:conf/ecsa/HaugwitzD15 fatcat:66cg3t23zffg3mfyygy4hvufp4

Reinforcement and shaping in learning action sequences with neural dynamics

Matthew Luciw, Yulia Sandamirskaya, Sohrob Kazerounian, Jurgen Schmidhuber, Gregor Schoner
2014 4th International Conference on Development and Learning and on Epigenetic Robotics  
Recently, we have introduced reinforcement learning in this framework, which allows an agent to learn goal-directed sequences of behaviours based on a reward signal, perceived at the end of a sequence.  ...  Here, we combine the neural dynamic reinforcement learning with shaping, which consists in providing intermediate rewards and accelerates learning.  ...  The latter architecture has integrated the DFT-based system for behavioural organization with the Reinforcement Learning algorithm (RL; [8] , [9] ), SARSA(λ).  ... 
doi:10.1109/devlrn.2014.6982953 dblp:conf/icdl-epirob/LuciwSKSS14 fatcat:plgzqhzlgvhprb72a5v26w254u

The Pig as a Model Animal for Studying Cognition and Neurobehavioral Disorders [chapter]

Elise T. Gieling, Teun Schuurman, Rebecca E. Nordquist, F. Josef van der Staay
2011 Current topics in behavioral neurosciences  
Mainly for rodents: well validated tests  Many not suited for / adapted to pigs Classification  Classical conditioning studies  'Pavlovian conditioning'  Operant conditioning (most) Yerkes  ...  This also accounts for cognitive testing  cognition is not a unitary function  involves multiple and dissociable systems that interact in cognitive processes  Learning through an aversive or appetitive  ... 
doi:10.1007/7854_2010_112 pmid:21287323 fatcat:7btqb4lk7fh6jcj5n22rvdfuqy

Treating selective mutism in a paediatric rehabilitation patient by altering environmental reinforcement contingencies

1999 Pediatric Rehabilitation  
The rehabilitation hospital setting, in which the patient is seen daily by multiple people in multiple settings, is particularly well-suited for implementing a systematic behavioural intervention to establish  ...  verbal behaviour and simultaneously reinforce its generalization.  ...  This pattern of behaviour might result from a learning history of positive reinforcement for non-verbal communication and punishment of attempts to speak.  ... 
doi:10.1080/136384999289595 pmid:10509352 fatcat:3ihknyqfkjbe7ecfly5oer762e

Kickstarting Deep Reinforcement Learning [article]

Simon Schmitt, Jonathan J. Hudson, Augustin Zidek, Simon Osindero, Carl Doersch, Wojciech M. Czarnecki, Joel Z. Leibo, Heinrich Kuttler, Andrew Zisserman, Karen Simonyan, S. M. Ali Eslami
2018 arXiv   pre-print
Kickstarting is conceptually simple and can easily be incorporated into reinforcement learning experiments.  ...  We present a method for using previously-trained 'teacher' agents to kickstart the training of a new 'student' agent.  ...  Acknowledgements We thank Lasse Espeholt, Hubert Soyer, and Chloe Hillier for helpful discussions, advice and support.  ... 
arXiv:1803.03835v1 fatcat:aj7ieldiwrb7nhu5ectlgh6sni

Moderate prenatal alcohol exposure was associated with a modest increase in adolescent learning and behavioural difficulties

W. L Hellerstedt
1998 Evidence-Based Nursing  
Moderate prenatal alcohol exposure was associated with a modest increase in adolescent learning and behavioural difficulties Olson HC, Streissguth AP, Sampson PD, et al.  ...  Association of prenatal alcohol exposure with behavioral and learning problems in early adolescence.  ...  None the less, the authors have addressed an important question and have reinforced the need for delineating alcohol specific outcomes, dose response effects, and the genetic or environmental factors that  ... 
doi:10.1136/ebn.1.2.56 fatcat:kjnkfk2btrcatndxzqx3ixfqey

Designing Deep Reinforcement Learning for Human Parameter Exploration

Hugo Scurto, Bavo Van Kerrebroeck, Baptiste Caramiaux, Frédéric Bevilacqua
2021 ACM Transactions on Computer-Human Interaction  
In this article, we propose to investigate artificial agents using deep reinforcement learning to explore parameter spaces in partnership with users for sound design.  ...  We also highlight varied user exploration behaviours throughout partnering with our system.  ...  ACKNOWLEDGMENTS We are grateful to our participants for their precious time and feedback.  ... 
doi:10.1145/3414472 fatcat:owxyc3nkojhtjczoetoa7pttdu

Learning to Transfer Role Assignment Across Team Sizes [article]

Dung Nguyen, Phuoc Nguyen, Svetha Venkatesh, Truyen Tran
2022 arXiv   pre-print
Multi-agent reinforcement learning holds the key for solving complex tasks that demand the coordination of learning agents.  ...  We demonstrate that re-using the role-based credit assignment structure can foster the learning process of larger reinforcement learning teams to achieve tasks requiring different roles.  ...  We evaluate our proposed framework on two suites of multi-agent reinforcement learning (MARL) experiments, highlighting the need for curriculum learning when solving strongly cooperative CTDE tasks.  ... 
arXiv:2204.12937v1 fatcat:25hcaf7o6rbo3nc3iyjw6eiyga

Learning to Change Together: The Social Context of Architectural Learning

Lara Mackintosh
2014 The International Journal of Arts Education  
Yet the social context of learning also affects the opportunities for such transformative learning experiences.  ...  In architectural education learning is often structured to inform and support change to sustainable design and behaviour.  ...  It allows for an understanding of the relations, actions and outcomes of learning, namely behaviour, to be developed.  ... 
doi:10.18848/2326-9944/cgp/v08i03/57-70 fatcat:ujxn62wjcbalxglkv37ghh3jri
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