João Balsa

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Tax compliance is a field that crosses over several research areas, from economics to machine learning, from sociology to artificial intelligence and multi-agent systems. The core of the problem is that the standing general theories cannot even explain why people comply as much as they do, much less make predictions or support prescriptions for the public(More)
In open societies such as multi-agent systems, it is important that coordination among the several actors is achieved efficiently. One economical way of capturing that aspiration is consensus: social conventions and lexicons are good examples of coordinating systems, where uniformity promotes shared expectations of behavior and shared meanings. We are(More)
Years ago, we addressed the issue of methodological procedures to develop the design of cognitive agents tuned to real problems, inserting them into a context where experimentation could have a meaningful outcome in terms of the original problems posed. Since then we have been building mechanisms and frameworks for mind design in multiagent systems. We(More)
A new methodology for overcoming incomplete information available for current natural language parsers will be presented in this paper. Although our aim is more ambitious, in this paper, we will focus on incomplete descriptions of the subcategorization classes of verbs and will sketch a proposal for overcoming the same problem for other syntactic(More)