Workshops

1. Formalizing Mechanisms for Artificial General Intelligence and Cognition (Formal MAGIC)

The “Formal MAGIC” workshop discusses the formalization of the most important cognitive mechanisms and human abilities that have already been shown in literature to play essential roles in computational models of artificial (general) intelligence, using available techniques like learning or reasoning.

Organizers: Ahmed M. H. Abdel-Fattah and Kai-Uwe Kühnberger (both from University of Osnabrück, Germany).

Accepted contribution:
C1: Ontological modeling of emotion-based decisions, by Daniele Porello, Roberta Ferrario, Cinzia Giorgetta
C2: Information Binding with Dynamic Associative Representations, by Naoya Arakawa
C3: Reductio ad Absurdum: On Oversimplification in Computer Science and its Pernicious Effect on Artificial Intelligence Research, by Kristinn R. Thórisson
C4: On Deep Computational Formalization of Natural Language, by Naveen Sundar Govindarajulu, Selmer Bringsjord, John Licato
C5: Formal Magic for Analogies, by Ulf Krumnack, Ahmed Abdel-Fattah, and Kai-Uwe Kühnberger
C6: Formal Models in AGI Research, by Pei Wang
C7: On Special Theory of Relativity of Function-an Interpretation to “the Failure of Equivalent Substitution Principle”, by Xiaolong Wan

Schedule:
First session (Cognition Engineering)
1: Keynote: Prof. Zhongzhi Shi [20 min] – Computational Model of Memory in CAM
2: Paper presentation (C1) [15 min] (including Q&A)
3: Paper presentation (C2) [15 min] (including Q&A)
4: Paper presentation (C3) [15 min] (including Q&A)
5: General Discussion: “Cognition Engineering” [20 min]
Second Session (Formalizations/Modeling)
1: Keynote: Prof. Stuart C. Shapiro [20 min] – Specifying Modalities in the MGLAIR Architecture
2: Paper presentation (C4) [15 min] (including Q&A)
3: Paper presentation (C7) [15 min] (including Q&A)
4: Paper presentation (C6) [15 min] (including Q&A)
5: General Discussion: “Formalizations/Modeling” [20 min]

For more information, visit the workshop webpage at http://cogsci.uni-osnabrueck.de/~formalmagic/

2. Probability Theory or Not? Practical and Theoretical  Concerns on Uncertainty Handling in AGI

In the emerging field of AGI, more and more researchers have realized the necessity of processing the uncertainty in the environment and the systems in a systematic and well-justified way. Many people choose to use the most developed mathematical theory, probability theory, to represent and process the uncertainty involved, although alternatives exist. Various mathematical models have been proposed, and many engineering designs also include probabilistic or statistical calculations in them.

Organizers: Matthew Ikle (Adams State University, USA) and Laurent Orseau (AgroParisTech, France)

Accepted papers:
C1- Comparing and weakening possibilistic knowledge bases, by Salem Benferhat
C2- Probability Theory Ensues from Assumptions of Approximate Consistency: A Simple Derivation and its Implications for AGI, by Ben Goertzel
C3- Direct Uncertainty Estimation in Reinforcement Learning, by Sergey Rodionov, Alexey Potapov, and Yurii Vinogradov
C4- Towards robust symbolic reasoning about information from the web, by Steven Schockaert
C5- Issues in Applying Probability Theory to AGI, by Pei Wang

Schedule:
First session:
Keynote: Steven Schockaert (C4) (30min)
1. Paper presentation (C1) – Benferhat (15min inc. technical Q&A)
2. Paper presentation (C3) – Rodionov, Potapov, Vinogradov (15min inc. technical Q&A)
3. Panel discussion (30min)
Second session:
Keynote: Marcus Hutter (Uncertainty & Induction in AGI) (30min)
1. Paper presentation (C2) – Goertzel (15min inc. technical Q&A)
2. Paper presentation (C5) – Wang (15min inc. technical Q&A)
3. Panel discussion (30min)

For more information, visit the workshop webpage at http://www.agroparistech.fr/mia/agi-workshop/.