@article {145, title = {A Hormone-Driven Epigenetic Mechanism for Adaptation in Autonomous Robots}, journal = {IEEE Transactions on Cognitive and Developmental Systems}, volume = {10}, year = {2018}, note = {Download (Open Access)}, pages = {445{\textendash}454}, publisher = {IEEE}, abstract = {Different epigenetic mechanisms provide biological organisms with the ability to adjust their physiology and/or morphology and adapt to a wide range of challenges posed by their environments. In particular, one type of epigenetic process, in which hormone concentrations are linked to the regulation of hormone receptors, has been shown to have implications for behavioral development. In this paper, taking inspiration from these biological processes, we investigate whether an epigenetic model based on the concept of hormonal regulation of receptors can provide a similarly robust and general adaptive mechanism for autonomous robots. We have implemented our model using a Koala robot, and tested it in a series of experiments in six different environments with varying challenges to negotiate. Our results, including the emergence of varied behaviors that permit the robot to exploit its current environment, demonstrate the potential of our epigenetic model as a general mechanism for adaptation in autonomous robots.}, issn = {2379-8920}, doi = {10.1109/TCDS.2017.2775620}, url = {https://ieeexplore.ieee.org/document/8115310/}, author = {Lones, John and Lewis, Matthew and Lola Ca{\~n}amero} } @article {2016, title = {Hedonic quality or reward? A study of basic pleasure in homeostasis and decision making of a motivated autonomous robot}, journal = {Adaptive Behavior}, volume = {24}, year = {2016}, note = {Download (Open Access)}, pages = {267{\textendash}291}, publisher = {SAGE}, abstract = {We present a robot architecture and experiments to investigate some of the roles that pleasure plays in the decision making (action selection) process of an autonomous robot that must survive in its environment. We have conducted three sets of experiments to assess the effect of different types of pleasure{\textemdash}related versus unrelated to the satisfaction of physiological needs{\textemdash}under different environmental circumstances. Our results indicate that pleasure, including pleasure unrelated to need satisfaction, has value for homeostatic management in terms of improved viability and increased flexibility in adaptive behavior.}, doi = {10.1177/1059712316666331}, url = {http://journals.sagepub.com/doi/full/10.1177/1059712316666331}, author = {Lewis, Matthew and Lola Ca{\~n}amero} } @inproceedings {2014, title = {Habit-based Regulation of Essential Variables}, booktitle = {Proc. 14th Conference on the Synthesis and Simulation of Living Systems (ALIFE 2014)}, year = {2014}, note = {Download}, pages = {168{\textendash}175}, publisher = {MIT Press}, organization = {MIT Press}, address = {New York, NY}, abstract = {A variety of models have been developed to investigate "homeostatic adaptation," a mechanism inspired by Ashby{\textquoteright}s homeostat, where a plastic control medium is reorganized until one or more essential variables are maintained within predefined limits. In these models, "habits" emerge, defined as behavior-generating mechanisms that rely upon their own influence to maintain the conditions necessary for their own persistence. In this paper, we present a recently developed sensorimotor-habit-based controller that is coupled to a simulated two-wheeled robot with a simulated metabolism. The simulation is used to demonstrate how habits can have the same essential variable(s) as the metabolic or "biological" organism that is performing the behavior, and that in certain conditions when this is the case, the emergent habits will tend to stabilize essential variables within viability limits. The model also demonstrates that an explicit pre-specification of (A) which variables should induce plasticity and (B) which values of those variables should induce plasticity is not always necessary for homeostatic adaptation of behavior.}, isbn = {978-0-262-32621-6}, doi = {10.7551/978-0-262-32621-6-ch029}, url = {https://www.mitpressjournals.org/doi/abs/10.1162/978-0-262-32621-6-ch029}, author = {Egbert, Matthew and Lola Ca{\~n}amero} } @inproceedings {2014, title = {Hormonal Modulation of Development and Behaviour Permits a Robot to Adapt to Novel Interactions}, booktitle = {Proc. 14th Conference on the Synthesis and Simulation of Living Systems (ALIFE 2014)}, year = {2014}, note = {Download}, pages = {184{\textendash}191}, publisher = {MIT Press}, organization = {MIT Press}, address = {New York, NY}, abstract = {Hormones are known to play a critical role in modulating the behaviour and development of organisms when confronted with different environment challenges. In this paper we present a biologically plausible hormonal mechanism that allows an autonomous robot to interact appropriately with novel objects and interactions depending upon both its current internal state and its past experiences. In our experiments, robots that had been exposed to negative experiences during their initial developmental phase displayed withdrawn behaviour and were less likely to explore new objects and environments, or to engage with a human caregiver. In contrast, robots with a positive upbringing showed much greater levels of outgoing behaviour such as exploration and social interaction.}, isbn = {978-0-262-32621-6}, doi = {10.7551/978-0-262-32621-6-ch031}, url = {https://www.mitpressjournals.org/doi/abs/10.1162/978-0-262-32621-6-ch031}, author = {Lones, John and Lewis, Matthew and Lola Ca{\~n}amero} } @inproceedings {2014, title = {Hormonal Modulation of Interaction Between Autonomous Agents}, booktitle = {Proc. 4th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics (ICDL-Epirob 2014)}, year = {2014}, note = {Download}, month = {10/2014}, pages = {402{\textendash}407}, publisher = {IEEE}, organization = {IEEE}, address = {Genoa, Italy}, abstract = {Epigenetic like mechanism potentially have a critical role to play in the long term modulation of behaviour, interaction and adaptation. In this study we implement an model of these mechanism, the upward and downward regulation of hormone receptors located in a simply hormone driven autonomous agent. We frame this study in a multi agent setup using competition as a way to change the dynamics of the environment and the challenges the agents face. We found that this simply epigenetic mechanism has the potential to significantly alter the behaviour of the agents, allowing them to develop not only unique individual behaviour but also group like structures that permit them to better adapt to the different challenges that the environment presents.}, doi = {10.1109/DEVLRN.2014.6983015}, url = {http://ieeexplore.ieee.org/document/6983015/}, author = {Lones, John and Lewis, Matthew and Lola Ca{\~n}amero} } @article {2013, title = {Hedonic Value: Enhancing Adaptation for Motivated Agents}, journal = {Adaptive Behavior}, volume = {21}, year = {2013}, note = {Download}, pages = {465{\textendash}483}, publisher = {SAGE}, abstract = {Reinforcement learning (RL) in the context of artificial agents is typically used to produce behavioural responses as a function of the reward obtained by interaction with the environment. When the problem consists of learning the shortest path to a goal, it is common to use reward functions yielding a fixed value after each decision, for example a positive value if the target location has been attained and a negative one at each intermediate step. However, this fixed strategy may be overly simplistic for agents to adapt to dynamic environments, in which resources may vary from time to time. By contrast, there is significant evidence that most living beings internally modulate reward value as a function of their context to expand their range of adaptivity. Inspired by the potential of this operation, we present a review of its underlying processes and we introduce a simplified formalisation for artificial agents. The performance of this formalism is tested by monitoring the adaptation of an agent endowed with a model of motivated actor-critic, embedded with our formalisation of value and constrained by physiological stability, to environments with different resource distribution. Our main result shows that the manner in which reward is internally processed as a function of the agent{\textquoteright}s motivational state, strongly influences adaptivity of the behavioural cycles generated and the agent{\textquoteright}s physiological stability.}, keywords = {Actor-Critic, Grounding, Hedonic Value, Motivation, Reinforcement Learning}, issn = {1059-7123}, doi = {10.1177/1059712313486817}, url = {https://journals.sagepub.com/doi/10.1177/1059712313486817}, author = {Ignasi Cos and Lola Ca{\~n}amero and Gillian M Hayes and Gillies, Andrew} } @inproceedings {2006, title = {Human Responses to an Expressive Robot}, booktitle = {Proceedings of the Sixth International Workshop on Epigenetic Robotics}, series = {Lund University Cognitive Studies}, volume = {128}, year = {2006}, pages = {79{\textendash}86}, publisher = {Lund University}, organization = {Lund University}, address = {Paris, France}, abstract = {This paper reports the results of the first study comparing subjects{\textquoteright} responses to robotic emotional facial displays and human emotional facial displays. It describes step by step the building of believable emotional expressions in a robotic head, the problems raised by a comparative approach of robotic and human expressions, and the solutions found in order to ensure a valid comparison. Twenty adults and 15 children aged 3 were presented static (photos) and dynamic (2-D videoclips, or 3-D live) displays of emotional expressions presented by a robot or a person. The study compares two dependent variables: emotional resonance (automatic facial feed-back during an emotional display) and emotion recognition (emotion labeling) according to partners (robot or person) and to the nature of the display (static or dynamic). Results for emotional resonance were similar with young children and with adults. Both groups resonated significantly more to dynamic displays than to static displays, be they robotic expressions or human expressions. In both groups, emotion recognition was easier for human expressions than for robotic ones. Unlike children that recognized more easily emotional expressions dynamically displayed, adults scored higher with static displays thus reflecting a cognitive strategy independent from emotional resonance. Results are discussed in the perspective of the therapeutic use of this comparative approach with children with autism that are described as impaired in emotion sharing and communication.}, isbn = {91-974741-6-9}, issn = {1101-8453}, url = {https://www.lucs.lu.se/LUCS/128/Nadeletal.pdf}, author = {Jacqueline Nadel and M Simon and P Canet and R Soussignan and P Blancard and Lola Ca{\~n}amero and Philippe Gaussier} } @inproceedings {2005, title = {Hormonal Modulation of Perception in Motivation-Based Action Selection Architectures}, booktitle = {Proceedings of the Symposium on Agents that Want and Like: Motivational and Emotional Roots of Cognition and Action (SSAISB{\textquoteright}05)}, year = {2005}, pages = {9{\textendash}16}, publisher = {AISB}, organization = {AISB}, address = {University of Hertfordshire, Hatfield, UK}, abstract = {The animat approach to artificial intelligence proposes biologically-inspired control mechanisms for autonomous robots. One of the related subproblems is action selection or what to do next . Many action selection architectures have been proposed. Motivation-based architectures implement a combination between internal and external stimuli to choose the appropriate behavior. Recent studies have pointed out that a second order mechanism to control motivation-based architectures would improve--dramatically their performance. Drawing on the notion of biological hormones we have modeled two of the functionalities ascribed to them in order to improve the adaptivity of motivation-based architectures. We have tested our hormone-like mechanisms in dynamic and unpredictable robotic scenarios. We analyze the results in terms of interesting behavioral phenomena that emerge from the interaction of these artificial hormones with the rest of architectural elements.}, isbn = {1-902956-41-7}, url = {https://www.aisb.org.uk/publications/proceedings/aisb2005/2_Agents_Final.pdf}, author = {Avila-Garc{\'\i}a, Orlando and Lola Ca{\~n}amero}, editor = {Lola Ca{\~n}amero} } @inproceedings {2000, title = {How Does It Feel? Emotional Interaction with a Humanoid LEGO Robot}, booktitle = {Socially Intelligent Agents: The Human in the Loop. Papers from the AAAI 2000 Fall Symposium}, year = {2000}, pages = {23{\textendash}28}, publisher = {AAAI Press}, organization = {AAAI Press}, address = {North Falmouth, Massachusetts}, abstract = {We report work on a LEGO robot capable of displaying several emotional expressions in response to physical contact. Our motivation has been to explore believable emotional exchanges to achieve plausible interaction with a simple robot. We have worked toward this goal in two ways. First, acknowledging the importance of physical manipulation in children{\textquoteright}s interactions, interaction with the robot is through tactile stimulation; the various kinds of stimulation that can elicit the robot{\textquoteright}s emotions are grounded in a model of emotion activation based on different stimulation patterns. Second, emotional states need to be clearly conveyed. We have drawn inspiration from theories of human basic emotions with associated universal facial expressions, which we have implemented in a caricaturized face. We have conducted experiments on children and adults to assess the recognizability of these expressions, and observed how people spontaneously interacting with Feelix respond to its emotional displays.}, isbn = {978-1-57735-127-6}, url = {http://www.aaai.org/Papers/Symposia/Fall/2000/FS-00-04/FS00-04-006.pdf}, author = {Ca{\~n}amero, Lola D and Fredslund, Jakob}, editor = {Kerstin Dautenhahn} } @article {1997, title = {A Hormonal Model of Emotions for Behavior Control}, year = {1997}, author = {D Ca{\~n}amero} }