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Profile: Giovanni Pezzulo (National Research Council of Italy)
  1. Giovanni Pezzulo, Matthijs A. A. van der Meer, Carien S. Lansink & Cyriel M. A. Pennartz (forthcoming). Internally Generated Sequences in Learning and Executing Goal-Directed Behavior. Trends in Cognitive Sciences.
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  2. Fabian Chersi, Marcello Ferro, Giovanni Pezzulo & Vito Pirrelli (2014). Topological Self‐Organization and Prediction Learning Support Both Action and Lexical Chains in the Brain. Topics in Cognitive Science 6 (3):476-491.
    A growing body of evidence in cognitive psychology and neuroscience suggests a deep interconnection between sensory-motor and language systems in the brain. Based on recent neurophysiological findings on the anatomo-functional organization of the fronto-parietal network, we present a computational model showing that language processing may have reused or co-developed organizing principles, functionality, and learning mechanisms typical of premotor circuit. The proposed model combines principles of Hebbian topological self-organization and prediction learning. Trained on sequences of either motor or linguistic units, the (...)
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  3. Giovanni Pezzulo (2014). Goals Reconfigure Cognition by Modulating Predictive Processes in the Brain. Behavioral and Brain Sciences 37 (2):154-155.
  4. Giovanni Pezzulo & Haris Dindo (2013). Intentional Strategies That Make Co-Actors More Predictable: The Case of Signaling. Behavioral and Brain Sciences 36 (4):371-372.
    Pickering & Garrod (P&G) explain dialogue dynamics in terms of forward modeling and prediction-by-simulation mechanisms. Their theory dissolves a strict segregation between production and comprehension processes, and it links dialogue to action-based theories of joint action. We propose that the theory can also incorporate intentional strategies that increase communicative success: for example, signaling strategies that help remaining predictable and forming common ground.
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  5. Giovanni Pezzulo (2011). Grounding Procedural and Declarative Knowledge in Sensorimotor Anticipation. Mind and Language 26 (1):78-114.
    We propose a view of embodied representations that is alternative to both symbolic/linguistic approaches and purely sensorimotor views of cognition, and can account for procedural and declarative knowledge manipulation. In accordance with recent evidence in cognitive neuroscience and psychology, we argue that anticipatory and simulative mechanisms, which arose during evolution for action control and not for cognition, determined the first form of representational content and were exapted for increasingly sophisticated cognitive uses. In particular, procedural and declarative forms of knowledge can (...)
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  6. Giovanni Pezzulo (2011). Shared Representations as Coordination Tools for Interaction. Review of Philosophy and Psychology 2 (2):303-333.
    Why is interaction so simple? This article presents a theory of interaction based on the use of shared representations as “coordination tools” (e.g., roundabouts that facilitate coordination of drivers). By aligning their representations (intentionally or unintentionally), interacting agents help one another to solve interaction problems in that they remain predictable, and offer cues for action selection and goal monitoring. We illustrate how this strategy works in a joint task (building together a tower of bricks) and discuss its requirements from a (...)
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  7. Giovanni Pezzulo & Cristiano Castelfranchi (2009). Thinking as the Control of Imagination: A Conceptual Framework for Goal-Directed Systems. Psychological Research 73 (4):559-577.
    This paper offers a conceptual framework which (re)integrates goal-directed control, motivational processes, and executive functions, and suggests a developmentalpathway from situated action to higher level cognition. We first illustrate a basic computational (control-theoretic) model of goal-directed action that makes use of internalmodeling. We then show that by adding the problem of selection among multiple actionalternatives motivation enters the scene, and that the basic mechanisms of executivefunctions such as inhibition, the monitoring of progresses, and working memory, arerequired for this system to (...)
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  8. Giovanni Pezzulo (2008). Coordinating with the Future: The Anticipatory Nature of Representation. [REVIEW] Minds and Machines 18 (2):179-225.
    Humans and other animals are able not only to coordinate their actions with their current sensorimotor state, but also to imagine, plan and act in view of the future, and to realize distal goals. In this paper we discuss whether or not their future-oriented conducts imply (future-oriented) representations. We illustrate the role played by anticipatory mechanisms in natural and artificial agents, and we propose a notion of representation that is grounded in the agent’s predictive capabilities. Therefore, we argue that the (...)
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  9. Giovanni Pezzulo & Gianguglielmo Calvi (2005). Dynamic Computation and Context Effects in the Hybrid Architecture Akira. In B. Kokinov A. Dey (ed.), Modeling and Using Context. Springer. 368--381.
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