Lexical Pragmatics and Theory of Mind: The Acquisition of Connectives

The concept of theory of mind (ToM), a hot topic in cognitive psychology for the past twenty-five years, has gained increasing importance in the fields of linguistics and pragmatics. However, even though the relationship between ToM and verbal communication is now recognized, the extent, causality and full implications of this connection remain mostly to be explored. This book presents a comprehensive discussion of the interface between language, communication, and theory of mind, and puts forward an innovative proposal regarding the role of discourse connectives for this interface. The proposed analysis of connectives is tested from the perspective of their acquisition, using empirical methods such as corpus analysis and controlled experiments, thus placing the study of connectives within the emerging framework of experimental pragmatics.

Learning in the cerebellar nucleus is necessary for acquisition of Pavlovian eyelid conditioning

The cumulative work presented here supports the hypothesis that plasticity in the cerebellar cortex and cerebellar nuclei mediates a simple associative form of motor teaming-Pavlovian eyelid conditioning. It was previously demonstrated that focal ablative lesions of cerebellar anterior lobe or pharmacological block of the cerebellar cortex output disrupted the timing of the conditioned eyeblink response, unmasking a response with a relatively fixed and very short latency to onset. The results of this thesis demonstrate that the short-latency responses are due to associative learning. Unpaired training does not support the acquisition of short-latency responses while the rate of acquisition of short-latency responses during paired training is approximately the same as that of timed conditioned responses. The acquisition of short-latency responses is dependent on an intact cerebellar cortex. Both ablative lesions of the cerebellar cortex and inactivation of cerebellar cortex output with picrotoxin block the acquisition of short-latency responses. However, once the short-latency responses are acquired neither disconnection of cerebellar cortex nor inactivation of the cerebellar nucleus block reacquisition. The results are consistent with the proposal that plasticity in the cerebellar cortex is necessary for learning the timing of conditioned responses, plasticity in the interpositus nucleus mediates the short latency responses, and cerebellar cortical output and mossy fiber input are necessary for the acquisition of short latency responses. ^

Autonomous Acquisition of Natural Situated Communication

An important part of human intelligence, both historically and operationally, is our ability to communicate. We learn how to communicate, and maintain our communicative skills, in a society of communicators – a highly effective way to reach and maintain proficiency in this complex skill. Principles that might allow artificial agents to learn language this way are in completely known at present – the multi-dimensional nature of socio-communicative skills are beyond every machine learning framework so far proposed. Our work begins to address the challenge of proposing a way for observation-based machine learning of natural language and communication. Our framework can learn complex communicative skills with minimal up-front knowledge. The system learns by incrementally producing predictive models of causal relationships in observed data, guided by goal-inference and reasoning using forward-inverse models. We present results from two experiments where our S1 agent learns human communication by observing two humans interacting in a realtime TV-style interview, using multimodal communicative gesture and situated language to talk about recycling of various materials and objects. S1 can learn multimodal complex language and multimodal communicative acts, a vocabulary of 100 words forming natural sentences with relatively complex sentence structure, including manual deictic reference and anaphora. S1 is seeded only with high-level information about goals of the interviewer and interviewee, and a small ontology; no grammar or other information is provided to S1 a priori. The agent learns the pragmatics, semantics, and syntax of complex utterances spoken and gestures from scratch, by observing the humans compare and contrast the cost and pollution related to recycling aluminum cans, glass bottles, newspaper, plastic, and wood. After 20 hours of observation S1 can perform an unscripted TV interview with a human, in the same style, without making mistakes.

Autonomous Acquisition of Natural Language

An important part of human intelligence is the ability to use language. Humans learn how to use language in a society of language users, which is probably the most effective way to learn a language from the ground up. Principles that might allow an artificial agents to learn language this way are not known at present. Here we present a framework which begins to address this challenge. Our auto-catalytic, endogenous, reflective architecture (AERA) supports the creation of agents that can learn natural language by observation. We present results from two experiments where our S1 agent learns human communication by observing two humans interacting in a realtime mock television interview, using gesture and situated language. Results show that S1 can learn multimodal complex language and multimodal communicative acts, using a vocabulary of 100 words with numerous sentence formats, by observing unscripted interaction between the humans, with no grammar being provided to it a priori, and only high-level information about the format of the human interaction in the form of high-level goals of the interviewer and interviewee and a small ontology. The agent learns both the pragmatics, semantics, and syntax of complex sentences spoken by the human subjects on the topic of recycling of objects such as aluminum cans, glass bottles, plastic, and wood, as well as use of manual deictic reference and anaphora.

On the acquisition of high-resolution maps with open source software and commercials off-the-shelf quad-rotors

Mosaics are high-resolution images obtained aerially and employed in several scientific research areas, such for example, in the field of environmental monitoring and precision agriculture. Although many high resolution maps are obtained by commercial demand, they can also be acquired with commercial aerial vehicles which provide more experimental autonomy and availability. For what regard to mosaicing-based aerial mission planners, there are not so many - if any - free of charge software. Therefore, in this paper is presented a framework designed with open source tools and libraries as an alternative to commercial tools to carry out mosaicing tasks.

The acquisition of skilled motor performance: Fast and slow experience-driven changes in primary motor cortex

Behavioral and neurophysiological studies suggest that skill learning can be mediated by discrete, experience-driven changes within specific neural representations subserving the performance of the trained task. We have shown that a few minutes of daily practice on a sequential finger opposition task induced large, incremental performance gains over a few weeks of training. These gains did not generalize to the contralateral hand nor to a matched sequence of identical component movements, suggesting that a lateralized representation of the learned sequence of movements evolved through practice. This interpretation was supported by functional MRI data showing that a more extensive representation of the trained sequence emerged in primary motor cortex after 3 weeks of training. The imaging data, however, also indicated important changes occurring in primary motor cortex during the initial scanning sessions, which we proposed may reflect the setting up of a task-specific motor processing routine. Here we provide behavioral and functional MRI data on experience-dependent changes induced by a limited amount of repetitions within the first imaging session. We show that this limited training experience can be sufficient to trigger performance gains that require time to become evident. We propose that skilled motor performance is acquired in several stages: “fast” learning, an initial, within-session improvement phase, followed by a period of consolidation of several hours duration, and then “slow” learning, consisting of delayed, incremental gains in performance emerging after continued practice. This time course may reflect basic mechanisms of neuronal plasticity in the adult brain that subserve the acquisition and retention of many different skills.