Notes:
Brain-emulating cognitive control architecture (BECCA) is a type of artificial intelligence (AI) system that is designed to mimic the cognitive processes of the human brain. BECCA systems are designed to be able to learn and adapt to new situations and tasks, and to make decisions and take actions based on their understanding of the environment and the goals of the system.
BECCA systems are typically based on artificial neural networks, which are computer algorithms that are inspired by the structure and function of the human brain. Neural networks are trained using large datasets and are able to learn patterns and relationships in the data. BECCA systems are designed to be able to learn and adapt in a similar way to the human brain, by adjusting the weights and connections of their neural network based on their experiences and observations.
BECCA systems are used in a variety of applications, including natural language processing, image recognition, and decision-making. They are particularly well-suited for tasks that require the ability to learn and adapt to new situations, and for tasks that require a high level of cognitive control, such as planning and decision-making.
Brain-emulating cognitive control architecture (BECCA) can be used in dialog systems to improve the natural language understanding and response generation capabilities of the system. BECCA systems are particularly well-suited for tasks that require learning and adaptability, such as natural language processing and decision-making, which are key components of many dialog systems.
In a dialog system, a BECCA system might be used to process user input and generate appropriate responses based on its understanding of the conversation context and the goals of the system. For example, a chatbot that is powered by a BECCA system might be able to understand and respond to user queries about a specific topic, or provide recommendations or suggestions based on the user’s preferences and past interactions with the system.
BECCA systems can also be used to improve the personalization and adaptability of dialog systems. For example, a BECCA-powered chatbot might be able to learn and adapt to a user’s preferences and style of communication over time, and tailor its responses accordingly. This can help to improve the user’s experience with the chatbot and make the conversation feel more natural and engaging.
Resources:
- github.com/matt2000/becca .. open-source artificial general intelligence platform
References:
See also:
Artificial Brains | Brain Simulation | HBP (Human Brain Project) 2011 | Robot Brains | Robot Brains 2011
BECCA: Reintegrating AI for Natural World Interaction. B Rohrer – AAAI Spring Symposium: Designing Intelligent Robots, 2012 – aaai.org Abstract Natural world interaction (NWI), the pursuit of arbitrary goals in unstructured physical environments, is an excellent motivating problem for the reintegration of artificial intelligence. It is the problem set that humans struggle to solve. At a minimum it entails … Cited by 4 Related articles All 7 versions
S-learning: A biomimetic algorithm for learning, memory, and control in robots B Rohrer – Neural Engineering, 2007. CNE’07. 3rd International …, 2007 – ieeexplore.ieee.org S-Learning: A Biomimetic Algorithm for Learning, Memory, and Control in Robots Brandon Rohrer … As the core of a Brain- Emulating Cognition and Control Architecture (BECCA), S- Learning provides a mechanism for human-inspired learning, memory, and control in machines. … Cited by 10 Related articles All 6 versions
Biologically inspired feature creation for multi-sensory perception. B Rohrer – BICA, 2011 – openbecca.org Page 1. Biologically inspired feature creation for multi-sensory perception Brandon ROHRER a,1 a Sandia National Laboratories, USA Abstract. … Together the feature creator and RL algorithm form BECCA, a brain-emulating cognition and control archi- tecture. … Cited by 8 Related articles All 10 versions
A developmental agent for learning features, environment models, and general robotics tasks B Rohrer – Joint IEEE International Conference on Development …, 2011 – openbecca.com … Brandon Rohrer Intelligent Systems, Robotics, and Cybernetics Group Sandia National Laboratories Albuquerque, New Mexico, USA Email: brrohre@sandia.gov Web: http://www.sandia.gov/˜brrohre Abstract—BECCA, a developmental agent, is described and … Cited by 7 Related articles All 5 versions
Efficient motion-based task learning N Malone, A Faust, B Rohrer, J Wood… – Robot Motion Planning …, 2012 – reflexxes.com … Computer Science, University of New Mexico, Albuquerque, NM 87131, {nmalone, afaust, tapia}@cs.unm.edu 2 Brandon Rohrer is with … is withThe Manufacturing Engineering Program, University of New Mexico, Albuquerque, NM 87131, jw@unm.edu BECCA development was … Cited by 5 Related articles All 5 versions
Implementation of an embodied general reinforcement learner on a serial link manipulator N Malone, B Rohrer, L Tapia, R Lumia… – … and Automation (ICRA …, 2012 – ieeexplore.ieee.org … Nicholas Malone, Brandon Rohrer, Lydia Tapia, Ron Lumia and John Wood Abstract—BECCA (a Brain-Emulating Cognition and Con- trol Architecture software package) was developed in order to perform general reinforcement learning, that is, to enable unmodeled embodied … Cited by 5 Related articles All 6 versions
An implemented architecture for feature creation and general reinforcement learning B Rohrer – Workshop on Self-Programming in AGI Systems, Fourth …, 2011 – sandia.gov … Brandon Rohrer Sandia National Laboratories, Intelligent Systems, Robotics, and Cybernetics Group, Albuquerque, NM, USA brrohre@sandia.gov http://www.sandia.gov/~brrohre Abstract. BECCA is a brain-emulating cognition and control architec- ture. … Cited by 2 Related articles All 6 versions
A Brain Emulating Cognition And Control Architecture B Rohrer, S Hulet – Progress in Biological Cybernetics Research, 2008 – books.google.com … Chapter 1 BECCA: A BRAIN EMULATING COGNITION AND CONTROL ARCHITECTURE Brandon Rohrer1* and Steven Hulet2 Intelligent Systems, Robotics, and Cybernetics Group Sandia National Laboratories, Albuquerque, NM, USA 2Computer Science Department … Cited by 11 Related articles All 7 versions
BECCA version 0.4. 4 User’s Guide B Rohrer – 2012 – sandia.gov Run benchmark. py in your Python interpreter. The benchmark. py module automatically runs BECCA on a collection of worlds that is included with the download. It gives a report of BECCA’s performance in the worlds. The benchmark can be used both to compare … Related articles All 4 versions
Final report for LDRD project 11-0783: directed robots for increased military manpower effectiveness. B Rohrer, JD Morrow, FH Rothganger, PG Xavier… – 2011 – prod.sandia.gov … B Rohrer, “BECCA code base” www.sandia.gov/rohrer/code.html , last updated … scripts provides all the code for the most recent version of BECCA and the … The consistent engagement with the academic community that the LDRD enabled allowed Brandon Rohrer to establish … All 2 versions
A Unified Architecture for Cognition and Motor Control Based on Neuroanatomy, Psychophysical Experiments, and Cognitive Behaviors. B Rohrer – AAAI Fall Symposium: Biologically Inspired Cognitive …, 2008 – aaai.org … Brandon Rohrer Intelligent Systems, Robotics, and Cybernetics Group Sandia National Laboratories ? MS 1010, PO Box 5800 Albuquerque, NM 87185-1010 Overview: A Brain-Emulating Cognition and Control Architecture (BECCA) is presented. … Related articles All 7 versions
Final report for LDRD project 11-0029: high-interest event detection in large-scale multi-modal data sets: proof of concept. B Rohrer – 2011 – prod.sandia.gov … Brandon Rohrer … One aspect of BECCA in particular was discovered to be critical to improved anomaly detection capabili- ties: it’s … B Rohrer, “Biologically inspired feature creation for multi-sensory perception,” Second International Conference on Biologically Inspired Cognitive … Related articles All 2 versions
Robust performance of autonomous robots in unstructured environments B Rohrer – Proceedings of the American Nuclear Society 2nd …, 2008 – sandia.gov … Brandon Rohrer Sandia National Laboratories: MS 1010, PO Box 5800, Albuquerque, NM 87185-1010, brrohre@sandia.gov … II.A. Architecture S-Learning is at the core of a biomimetic Brain- Emulating Cognition and Control Architecture (BECCA, Fig. … Cited by 3 Related articles All 5 versions
Concepts from Data. B Rohrer, JD Morrow, F Rothganger… – AAAI Fall Symposium: …, 2009 – aaai.org … Brandon Rohrer ? , J. Dan Morrow, Fred Rothganger, and Patrick G. Xavier Sandia National Laboratories PO Box 5800, MS 1010 Albuquerque, New Mexico 87185 … read in sensor data, and create the de- cision tree can be found at (Rohrer 2009a) in the package “becca SRV”. … Cited by 3 Related articles All 5 versions
Reinforcement Learning as a Local Planner-A Survey A Faust – cs.unm.edu … “Reinforcement Learning as a Local Planner – A Survey”, Faust, Univ. of New Mexico, December 2012 2 3.4 Becca Brandon [17], [18], [19] 4 Planning in Continuous Domains … pancake[8] -table tennis [14] 5.2.2 Becca Nick’s IROS paper – [12] Nick’s ICRA paper – [13] Page 4. … Related articles
[BOOK] Progress in Biological Cybernetics Research DA De Jong – 2008 – books.google.com … Contents Preface Chapter 1 Chapter 2 Chapter 3 Chapter 4 Chapter 5 Chapter 6 BECCA: A Brain Emulating Cognition and Control Architecture Brandon Rohrer and Steven Hulet The Lur’e Framework for Modeling and Analysis of Neuronal Oscillator T. Iwasaki and M. Zheng … All 2 versions
Toward a Unified Catalog of Implemented Cognitive Architectures. AV Samsonovich – BICA, 2010 – books.google.com … Names of its contributors (sorted alphabetically by the represented architecture name) are: James S. Albus (4D/RCS), Christian Lebiere and Andrea Stocco (ACT-R), Stephen Grossberg (ART), Brandon Rohrer (BECCA), Balakrishnan Chandrasekaran and Unmesh Kurup … Cited by 30 Related articles All 6 versions
BICA 2010 ABSTRACTS IJM Conscious – Int. J. Mach. Conscious, 2010 – World Scientific … Keywords: cognitive robotics; neural networks; genetic algorithms; nonlinear dynamics. 23. BECCA: A BICA for Arbitrary Robots in Unknown Worlds. Brandon Rohrer (Sandia National Laboratories, Albuquerque, New Mexico, USA: brrohre@sandia.gov) …
Reinforcement learning as a motion planner—a survey A Faust – 2012 – academia.edu … 3.3 BECCA Another paradigm for solving planning problems in unknown environments is BECCA. It is an unsu- pervised hierarchical feature extractor paired with a model-based reinforcement learner [20] [21]. … A good descrip- tion of BECCA is found in [14]. … Cited by 1 Related articles All 2 versions
[BOOK] Biological Cybernetics Research Trends TO Williams – 2007 – books.google.com Page 1. Biological Cybernetics Research Trends Contributors Kareem I. Batarseh Yury P. Shimansky Andreas Hofmann AHG van den Broeke Sungho Jo FCT van der Helm HFJM Koopman BW Verdaasdonk Thomas 0. Williams Editor Page 2. Page 3. Page 4. Page 5. …
A formalism for learning from demonstration EA Billing, T Hellström – Paladyn, 2010 – Springer Page 1. PALADYN Journal of Behavioral Robotics Research Article · DOI: 10.2478/s13230-010-0001-5 · JBR · 1(1) · 2010 · 1-13 A Formalism for Learning from Demonstration? Erik A. Billing† , Thomas Hellström‡ Department … Cited by 22 Related articles All 10 versions
Behavior recognition for learning from demonstration EA Billing, T Hellstrom, L Janlert – Robotics and Automation ( …, 2010 – ieeexplore.ieee.org Page 1. Behavior Recognition for Learning from Demonstration Erik A. Billing Department of Computing Science Umeå University Umeå, Sweden Email: billing@cs.umu.se Thomas Hellström Department of Computing Science … Cited by 12 Related articles All 6 versions
Full View Cognitive architectures and autonomy: Commentary and Response C Castelfranchi – Journal of Artificial General Intelligence, 2012 – cfwebprod.sandia.gov … Page 15. COGNITIVE ARCHITECTURES AND AUTONOMY: COMMENTARY AND RESPONSE 45 An Appeal for Declaring Research Goals Brandon Rohrer BROHRER@ GMAIL.COM Sandia National Laboratories Albuquerque, NM 87185, USA … All 3 versions
Learning General Features From Images and Audio With Stacked Denoising Autoencoders. NH Nifong – 2013 – pdxscholar.library.pdx.edu … 2.7 Relevant work Brandon Rohrer at Sandia National Laboratories developed a model which learned abstract features from images and audio known as BECCA [?]. It is inspired by the properties of the visual cortex, and attempts to re-create the visual cortex’s generality … Related articles All 2 versions
Predictive learning from demonstration EA Billing, T Hellström, LE Janlert – Agents and Artificial Intelligence, 2011 – Springer … work. Acknowledgements We would like to thank Brandon Rohrer at Sandia National Laboratories and Christian Balkenius at Lund University for valuable input to this work. References 1. Arkin, RC: Behaviour-Based Robotics. … Cited by 1 Related articles All 10 versions
Model-free Learning from Demonstration. EA Billing, T Hellström, LE Janlert – ICAART (2), 2010 – diva-portal.org Page 1. DiVA – Digitala Vetenskapliga Arkivet http://umu.diva-portal. org _____ This is an author produced version of … Cited by 3 Related articles All 5 versions
Cognition Rehearsed: Recognition and Reproduction of Demonstrated Behavior E Billing – 2012 – diva-portal.org … together. About the same time, Ben Edin5, supervisor for my Master Thesis, directed me to the work by Brandon Rohrer at Sandia National Laboratories. … research. I also acknowledge Brandon Rohrer for valuable input to this work. … Related articles All 3 versions