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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 8

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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 11

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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 16

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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. 18

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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