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Pezzulo G.,CNR Institute of Computational linguistics Antonio Zampolli | Pezzulo G.,CNR Institute of Cognitive Sciences and Technologies | Dindo H.,University of Palermo
Behavioral and Brain Sciences | Year: 2013

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. Copyright © 2013 Cambridge University Press. Source

Gigliotta O.,University of Naples Federico II | Pezzulo G.,CNR Institute of Computational linguistics Antonio Zampolli | Nolfi S.,CNR Institute of Neuroscience
Theory in Biosciences | Year: 2011

We show how simulated robots evolved for the ability to display a context-dependent periodic behavior can spontaneously develop an internal model and rely on it to fulfill their task when sensory stimulation is temporarily unavailable. The analysis of some of the best evolved agents indicates that their internal model operates by anticipating sensory stimuli. More precisely, it anticipates functional properties of the next sensory state rather than the exact state that sensors will assume. The characteristics of the states that are anticipated and of the sensorimotor rules that determine how the agents react to the experienced states, however, ensure that they produce very similar behaviour during normal and blind phases in which sensory stimulation is available or is self-generated by the agent, respectively. Agents' internal models also ensure an effective transition during the phases in which agents' internal dynamics is decoupled and re-coupled with the sensorimotor flow. Our results suggest that internal models might have arisen for behavioral reasons and successively exapted for other cognitive functions. Moreover, the obtained results suggest that self-generated internal states should not necessarily match in detail the corresponding sensory states and might rather encode more abstract and motor-oriented information. © 2011 Springer-Verlag. Source

Del Grosso A.M.,CNR Institute of Computational linguistics Antonio Zampolli
MMEDIA 2013 - 5th International Conferences on Advances in Multimedia | Year: 2013

This paper aims at illustrating a collaborative and modular web platform in the domain of digital and computational philology. The proposed work deals with parallel multilingual and multimedia resources. Two case studies are discussed in order to show the flexibility of the designed platform. The reusability of the components in different projects is achieved by abstract modeling and through the application of effective design patterns. The platform deals with textual resources and associated multimedia content, which can be retrieved by the metadata and shown in parallel (e.g., the page image of a manuscripts and the related transcription). The library of components will distribute under GPL 3.0 license and available at https://github.com/CoPhi. Source

Pezzulo G.,CNR Institute of Computational linguistics Antonio Zampolli | Pezzulo G.,CNR Institute of Cognitive Sciences and Technologies | Rigoli F.,CNR Institute of Cognitive Sciences and Technologies | Rigoli F.,University of Siena
Frontiers in Neuroscience | Year: 2011

Traditional theories of decision-making assume that utilities are based on the intrinsic value of outcomes; in turn, these values depend on associations between expected outcomes and the current motivational state of the decision-maker. This view disregards the fact that humans (and possibly other animals) have prospection abilities, which permit anticipating future mental processes and motivational and emotional states. For instance, we can evaluate future outcomes in light of the motivational state we expect to have when the outcome is collected, not (only) when we make a decision. Consequently, we can plan for the future and choose to store food to be consumed when we expect to be hungry, not immediately. Furthermore, similarly to any expected outcome, we can assign a value to our anticipated mental processes and emotions. It has been reported that (in some circumstances) human subjects prefer to receive an unavoidable punishment immediately, probably because they are anticipating the dread associated with the time spent waiting for the punishment. This article offers a formal framework to guide neuroeconomic research on how prospection affects decision-making. The model has two characteristics. First, it uses model-based Bayesian inference to describe anticipation of cognitive and motivational processes. Second, the utility-maximization process considers these anticipations in two ways: to evaluate outcomes (e.g., the pleasure of eating a pie is evaluated differently at the beginning of a dinner, when one is hungry, and at the end of the dinner, when one is satiated), and as outcomes having a value themselves (e.g., the case of dread as a cost of waiting for punishment). By explicitly accounting for the relationship between prospection and value, our model provides a framework to reconcile the utility-maximization approach with psychological phenomena such as planning for the future and dread. © 2011 Pezzulo and Rigoli. Source

Chersi F.,CNR Institute of Neuroscience | Pezzulo G.,CNR Institute of Neuroscience | Pezzulo G.,CNR Institute of Computational linguistics Antonio Zampolli
Cognitive Processing | Year: 2012

The hippocampus plays a central role in spatial representation, declarative and episodic memory. In this area, so-called place cells possess high spatial selectivity, firing preferentially when the individual is within a small area of the environment. Interestingly, it has been found in rats that these cells can be active also when the animal is outside the location or context of their corresponding place field producing so-called "forward sweeps". These typically occur at decision points during task execution and seem to be utilized, among other things, for the evaluation of potential alternative paths. Anticipatory firing is also found in the ventral striatum, a brain area that is strongly interconnected with the hippocampus and is known to encode value and reward. In this paper, we describe a biologically based computational model of the hippocampal-ventral striatum circuit that implements a goal-directed mechanism of choice, with the hippocampus primarily involved in the mental simulation of possible navigation paths and the ventral striatum involved in the evaluation of the associated reward expectancies. The model is validated in a navigation task in which a rat is placed in a complex maze with multiple rewarding sites. We show that the rat mentally activates place cells to simulate paths, estimate their value, and make decisions, implementing two essential processes of model-based reinforcement learning algorithms of choice: look-ahead prediction and the evaluation of predicted states. © 2012 Marta Olivetti Belardinelli and Springer-Verlag. Source

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