Doctoral Research Seminar Towards an Integrative Computational Foundation for Applied Behavior Analysis in Early Autism Interventions Edmon Begoli, EECS, March 2013 1
Transcript
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Doctoral Research Seminar Towards an Integrative Computational
Foundation for Applied Behavior Analysis in Early Autism
Interventions Edmon Begoli, EECS, March 2013 1
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Outline Motivation Introduction, background and related work
Hypothesis Approach Contribution Related Work 2
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Motivation Domain - impact and prevalence of Autism Idea*
natural language based knowledge representation as an integrative
foundation (thesis) Application Socially Assistive Robotics [2] and
Intelligent Agents * - get a feedback on an idea 3
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Prevalence of Autism 1 in 88 children diagnosed with Autism
every year Increasingly diagnosed condition is a major, lifelong
challenge for individuals, families, communities, educational and
healthcare system Harvard School of Medicine study from 2006 found
that lifetime cost of autism condition can be up to $3.2 million
per individual during lifetime. (cumulatively $32 billion a year
and increasing) No cure, but number of interventions, specially in
early childhood offer great promise and results Evidence based
behavioral interventions have proven as effective, early
intervention methods 4
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Applied Behavioral Analysis (ABA) [1] The science of the human
behavior (formerly known as behavior modification) Design,
implementation, and evaluation of environmental modifications to
produce socially significant improvement in human behavior Analysis
based on direct observation, measurement, and functional analysis
of the relations between environment and behavior Uses antecedent
stimuli and consequences, based on the findings of descriptive and
functional analysis, to produce practical change 5
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ABA in Special Education 6
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ABA Process selection of interfering behavior or behavioral
skill deficit(s) identification of goals and objectives
establishment of a method of measuring target behaviors evaluation
of the current levels of performance (baseline) design and
implementation of the interventions that teach new skills and/or
reduce interfering behaviors continuous measurement of target
behaviors to determine the effectiveness of the intervention, and
ongoing evaluation of the effectiveness of the intervention, with
modifications made as necessary to maintain and/or increase both
the effectiveness and the efficiency of the intervention. 7
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Seven Dimensions of ABA 1.Applied 2.Behavioral 3.Analytic
4.Technological 5.Conceptually Systematic 6.Effective 7.Generality
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ABA and its Effectiveness Applied Behavior Analysis (ABA) is
the process aimed at improving socially significant behaviors.
According to American Journal of Pediatrics intensive ABA was found
to be the most effective of all intensive behavioral therapies in
Autism ABA is not specific to Autism, but it has been applied in
this field with great success ABA is a family of therapies:
Discrete Trial Training, Pivotal Response Training ABA is
effective, but weekly requirements for therapy (20-40 hrs) are hard
to afford and fulfill 9
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ABA-Discrete Trial Structure S d R S r 1.Cue S d -
discriminative stimulus (also called Antecedent) 2.Prompt is a
supplemental teaching aid aimed at assisting students in responding
correctly to the cue. 1.Response (R) is students correct or
incorrect response to the instructors cue. 1.Consequence (S r ) for
a correct or incorrect response. 1.Inter-trial interval time
allowed to elapse between the two trials 10
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Discrete Trial Training Script Sample Independent Trial Teacher
places one red and one blue card on the table, then says point to
red Teacher gives no prompt (independent) Jane responds by pointing
to the red card The teacher would say Thats right! Well done! There
would be a very short pause before a new discrete trial would begin
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Computer Science and Autism Therapies Socially Assistive Robots
SAR [2] Mixed Reality Agents MR [3] Virtual (UF) Physical (BYU)
Apps and applications 12
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Socially Assistive Robotics 13
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Interdisciplinary Gap Psychology - Theory Special Education -
Practice Neuroscience - Neurobiology Computer Science and
Electrical Engineering Computational Methods and Robotics What
unifies them? 14
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Hypothesis ABA-based therapies are well suited for
computational formalization. The structure and governing principles
of ABA can be represented as a process ontology. Use controlled
natural language as a human user friendly medium of formal
knowledge representation and as an ontology language. 15
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Basis for Hypothesis Principles of behavioral science make ABA
amenable to computational representation: Three-term contingency
(ABC) Antecedent, Behavior, Consequence Behavioral scripts Prompt,
cue, fading, intra-trial interval, chaining if-then-else and loop
structures of ABC Data driven progression and measurements
(Functional Behavioral Analysis (FBA)) Software specification-like
dimensions of ABA Technological scripting and repeatability
Analytic based on measurements and testable hypothesis Controlled
Natural Languages Early findings from SAR Children are comfortable
with non-human agents Three roles for robots proxy, therapist, toy
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Approach and Research Plan Research ABA theory and therapies
Develop ABA representational formalism - ( - calculus) Establish
representational and translational technology Evaluate and validate
Use DTT as a proof-of-concept Validate against competency questions
[10] Run simplistic agent-based simulation 17
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Knowledge Representation and Reasoning (KRR), Ontologies Davis
et al[8] define KRR through these roles: 1.Surrogate for the actual
phenomena it represents 2.Set of ontological commitments
3.Fragmentary theory of intelligent reasoning 4.Medium for
pragmatically efficient computation 5.Medium of human expression
Ontology is an explicit formal specification of how to represent
the objects, concepts and other entities that are assumed to exist
in some area of interest and the relationships that hold among
them. Process ontology is a description of the participants
(components) and their relationships that make up a process.
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-Calculus a logic formalism for ABA dynamics Three term
contingency: A->B->C Chaining (forward and backward)
Prompting Thining (prompt) Shaping Fading (reinforcement)
Foundations in Situation [8] and Event [9] calculus 19
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Attempto Controlled English (ACE) Ontology Language A recent
and actively used CNL (there are dozens) Formalization by Kuehn in
his thesis [6], [7] ACE Assistive editor, RACE consistency checker,
AceWiki Integration with WordNet and other upper ontologies
Exportable to RDF, OWL, OWL2 20
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ACE Editor 21
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ACE Reasoner (RACE) 22
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Validation Competency Questions [10] Formal capture and
verification of - calculus through ACE Editor and RACE Agent Model
and Experimentation 23
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Outcome and Contribution Novelty in Computer Science ABA
formalism ( -calculus) CNL as process ontology language for ABA
Benefits ABA specification writeable and readable by humans
Understandable by computer scientists and educators Machine
process-able specification Broader Societal Contribution could
potentially reduce the burden and cost of early behavioral
interventions and improve availability and access to ABA
therapeutic resources 24
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References 1.Cooper, J. O., Heron, T. E., & Heward, W. L.
(2007). Applied behavior analysis (pp. 219223). Upper Saddle River,
NJ: Merrill. 2.Feil-Seifer, D., & Mataric, M. J. (2011).
Socially assistive robotics. Robotics & Automation Magazine,
IEEE, 18(1), 24-31. 3.Milgram, P., & Kishino, F. (1994). A
taxonomy of mixed reality visual displays.IEICE TRANSACTIONS on
Information and Systems, 77(12), 1321- 1329. 4.Davis, R., Shrobe,
H., & Szolovits, P. (1993). What is a knowledge
representation?. AI magazine, 14(1), 17. 5.Gruninger, M., &
Menzel, C. (2003). The process specification language (PSL) theory
and applications. AI magazine, 24(3), 63. 6.Kuhn, T. (2010).
Controlled English for Knowledge Representation (Doctoral
dissertation, PhD thesis, Faculty of Economics, Business
Administration and Information Technology of the University of
Zurich). 7.Fuchs, N., Kaljurand, K., & Kuhn, T. (2008).
Attempto controlled english for knowledge representation. Reasoning
Web, 104-124. 8.Levesque, H., Pirri, F., & Reiter, R. (1998).
Foundations for the situation calculus. Linkping Electronic
Articles in Computer and Information Science,3(18). 9.Shanahan, M.
(1999). The event calculus explained. Artificial intelligence
today, 409-430. 10.Gruninger, M., & Fox, M. S. (1994, June).
The role of competency questions in enterprise engineering. In
Proceedings of the IFIP WG5 (Vol. 7, pp. 212-221). 25