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Panel Discussion I: Brainstorm on Language, Embodiment and the Critical minass of Intelligence Moderator: Alexei Samsonovich Panelists: Kenneth De Jong,

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Presentation on theme: "Panel Discussion I: Brainstorm on Language, Embodiment and the Critical minass of Intelligence Moderator: Alexei Samsonovich Panelists: Kenneth De Jong,"— Presentation transcript:

1 Panel Discussion I: Brainstorm on Language, Embodiment and the Critical minass of Intelligence Moderator: Alexei Samsonovich Panelists: Kenneth De Jong, Dennis Perzanowski, Stuart Shapiro, Ralph Weischedel, Antonio Chella, Wei Chen, Roberto Pirrone, Christian Lebiere

2 Objective: Agenda: Samsonovich3 min Language acquisition by children Perzanowski5 min Goertzel5 min Weischedel5 min Bridging the gaps Lebiere5 min Chella5 min Shapiro5 min Identifying a critical mass Chen5 min Pirrone5 min De Jong5 min Response from the audience general discussion12 min To identify a sufficient language component of a super-critical mass of intelligence and embodiment that would enable a bootstrapped cognitive growth of an artifact up to a human level of general intelligence Introduction

3 language acquisition by children

4 Questions to Dennis Perzanowski: The work of Deb Roy directed at learning how children acquire language implies understanding the cognitive steps and stages of develoopment, and then emulating and embodying them on robotic platforms. – What should we borrow from these studies of the acquisition of language by young children? – E.g., how the agent will develop an understanding of concepts associated with linguistic constructs?

5 Questions to Ralph Weischedel: If language is the key to the human mind, then understanding the process of language acquisition could be the key to developing human-level intelligence. Specific questions include: – What should we borrow from studies of the acquisition of language by young children? – E.g., how the agent will develop an understanding of concepts associated with linguistic constructs? See next 3 slides prepared by Ralph Weischedel

6 6 What should we borrow from studies of the acquisition of language by young children? Ralph Weischedel November 7, 2008

7 7 An Interesting Question, Given History 70s-80s –Computational Linguistics –Hand-crafted rules –Reason from a handful of examples/counter-examples 90s –Natural Language Processing –Statistical learning approaches –Empirical evaluation on blind test data 2000s –90s + –Semi-supervised learning from WWW 2010s? –Inspiration of child language acquisition?

8 8 What should we Borrow from Child Language Acquisition? Positively Inspiring Leaning paradigm –Training data Image/video + description Touch (+ description) –Output capability Brief utterances Actions (move, touch, push) Simultaneous generalization in multiple spaces –Image space Forming object/activity class –Speech signal –Lexicon What might be innate (and built in for a system) Children interact with –Care-givers –Environment Not Biologically Bound Machines have vast amount of information (text, images and, video) online –A basis for unsupervised learning

9 One reply from the audience

10 Bridging the gaps

11 Questions to Christian Lebiere: The relation between language and the cognitive architecture, including its basic components, memory systems, kinds of representations, and principles of information processing. Specific questions include: – Is language processing an underlying capacity for other faculties like symbolic processing, or vice versa? – What kinds of architectural mechanisms should be involved in language processing?

12 Questions to Antonio Chella: The kinds of representation and information processing needed for the critical mass. Specific questions include: – What is the missing link between the following two levels of representations? (i) The higher symbolic level that underlies language, reasoning, attention control, planning and decision making. (ii) The lower subsymbolic level associated with neural network dynamics and signal processing. – Is this missing link a missing component of the critical mass? – How the conceptual spaces proposed by Gärdenfors (2000) may allow us to bridge this gap?

13 Questions to Stuart Shapiro: An example of a potential critical mass: GLAIR architecture that uses symbols in the Knowledge Layer as "pivots" that each may be aligned with one or more bodily modalities. Thus, one can identify (in NL) and manipulate what one sees, or one may find in the environment what one hears about (via NL). More work is still needed on self-awareness, and on identifying the basic cognitive building blocks that underlie all languages and cultures, and that therefore allow an intelligent agent to learn any language and culture it is brought up in. Specific questions include: – What are the general critical mass requirements for the embodiment and the interface, including environment, domain, perception and action capabilities? – What are the general critical mass requirements for the communication capabilities, including initial natural language capabilities? – What are the general critical mass requirements for the "innate" (pre-programmed) general knowledge? See next 3 slides prepared by Stuart Shapiro

14 KL (SNePS) PMLa PMLb PMLc SAL Mind Body Independent of lower-body implementation Hearing Vision Motion Speech WORLDWORLD I/P s o c k e t s MGLAIR Agent Architecture Dependent on lower-body implementation Proprioception

15 Alignment KL Body (PML/SAL) World SNePS term PML structure Object/PhenomenonAction

16 Jackendoff Version Ray Jackendoff, Foundations of Language, Oxford University Press, 2002, Fig. 11.1, p. 348. (Independent work)

17 One reply from the audience

18 Identifying a (super)critical mass

19 Questions to Wei Chen: The critical mass of linguistic, cognitive and interface capabilities that will enable cognitive growth of an artifact. Specific questions include: – What are the general critical mass requirements for the memory systems, kinds of representations and principles of information processing? – What are the general critical mass requirements for the communication capabilities, including initial natural language capabilities? – What are the general critical mass requirements for the "innate" (pre-programmed) general knowledge?

20 Questions to Roberto Pirrone: The connection between language in AI and educational sciences, specifically, language understanding techniques used in education. Specific questions include: – What is the applicability of Cognitive Linguistics techniques to the task of understanding language in educational practice? – What is the need for a language understanding component in a framework for student tutoring, and how this component should be implemented?

21 Questions to Kenneth De Jong: The notion of a critical mass apparently involves higher cognitive abilities like metacognition and the sense of self. – Can we identify a (super)critical mass in terms of higher cognitive abilities? – What is the connection with other aspects, e.g., linguistic and evolutionary requirements?

22 General discussion and conclusions "Critical mass" can be understood as a minimal set of intelligent capabilities and features of embodiment, such that, when integrated in an artifact, together will enable its cognitive growth up to a human level via teaching, social interactions and guided exploration of knowledge resources and environments. Then what, in your view, are its critical components, and how close we are to creating them? What can you say regarding "the ladder", i.e., the curriculum for artifacts understood as the sequence of tasks, paradigms and intermediate learning goals that will scaffold their rapid cognitive growth up to the human level? Can you imagine a successful cognitive growth scenario: e.g., as initially discussed within BICA program, from a simple egg hunt to a general human level of intelligence? Reproducing the cognitive growth phenomenon in a lab is a fundamental scientific problem. The expected phenomenon, however, has a known biological counterpart: child development. What should we borrow from biological, cognitive, educational, social, etc. sciences in order to ensure success? How can we imagine a roadmap to human-level-intelligent artifacts? What would be a sequence of waypoints and a realistic timetable for reaching them? What should be the cost of the project?


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