Exploring Data-Driven Components of Socially Intelligent AI through Cooperative Game Paradigms

The development of new approaches for creating more “life-like” artificial intelligence (AI) capable of natural social interaction is of interest to a number of scientific fields, from virtual reality to human–robot interaction to natural language speech systems. Yet how such “Social AI” agents might be manifested remains an open question. Previous research has shown that both behavioral factors related to the artificial agent itself as well as contextual factors beyond the agent (i.e., interaction context) play a critical role in how people perceive interactions with interactive technology. As such, there is a need for customizable agents and customizable environments that allow us to explore both sides in a simultaneous manner. To that end, we describe here the development of a cooperative game environment and Social AI using a data-driven approach, which allows us to simultaneously manipulate different components of the social interaction (both behavioral and contextual). We conducted multiple human–human and human–AI interaction experiments to better understand the components necessary for creation of a Social AI virtual avatar capable of autonomously speaking and interacting with humans in multiple languages during cooperative gameplay (in this case, a social survival video game) in context-relevant ways

Clinical features and outcomes in spontaneous intramural small bowel hematoma: cohort study and literature review

Background/Aims Spontaneous intramural small bowel hematoma (SISBH) is an extremely rare complication of anticoagulant or antiplatelet therapy. We assessed the clinical characteristics and outcomes of patients with SISBH according to the anatomical location of the hematoma. Methods From January 2003 to February 2016, medical records for all patients hospitalized for SISBH at 2 tertiary referral hospitals were retrospectively reviewed. The primary outcome was requirement for surgery. Results A total of 37 patients were enrolled. The mean age was 74.1 years. Among them, 33 patients (89.2%) were taking anticoagulant and/or antiplatelet agents. Duodenal intramural hematoma was detected in 4 patients (10.8%), jejunal in 16 (43.2%), and ileal in 17 (45.9%). Compared to jejunal and ileal involvement, duodenal intramural hematoma was significantly associated with high Charlson comorbidity index and low levels of white blood cells, hemoglobin, and platelets in the blood. SISBH in the duodenum was related to thrombocytopenia in 3 patients following systemic chemotherapy for malignancy. All patients with SISBH showed clinical improvement with conservative therapy. Mean length of hospital stay was 9.35 days. Independent predictors of a hospital stay of more than 7 days were body weight less than 60 kg (odds ratio [OR], 12.213; 95% confidence interval [CI], 1.755–84.998; P=0.011) and a history of cerebrovascular accidents (OR, 6.667; 95% CI, 1.121–39.650; P=0.037). Conclusions Compared to jejunal and ileal involvement, thrombocytopenia may result in spontaneous duodenal intramural hematoma among patients who are treated with systemic chemotherapy for malignancies. Patients with SISBH have excellent clinical outcomes with conservative therapy regardless of the anatomical location of the hematoma

Real-Time Video Stitching Using Camera Path Estimation and Homography Refinement

We propose a novel real-time video stitching method using camera path estimation and homography refinement. The method can stably stitch multiple frames acquired from moving cameras in real time. In the proposed method, one initial between-camera (BC) homography and each camera path (CP) homography are used to estimate the BC homography at every frame. The BC homography is refined by using block matching to adjust the errors of estimated CPs (homography refinement). For fast processing, we extract features using the difference of intensities and use the optical flow to estimate camera motion (CM) homographies, which are multiplied with the previous CMs to calculate CPs (camera path estimations). In experiments, we demonstrated the performance of the CP estimation and homography refinement approach by comparing it with other methods. The experimental results show that the proposed method can stably stitch two image sequences at a rate exceeding 13 fps (frames per second)

A Memetic Algorithm with a Novel Repair Heuristic for the Multiple-Choice Multidimensional Knapsack Problem

We propose a memetic algorithm for the multiple-choice multidimensional knapsack problem (MMKP). In this study, we focus on finding good solutions for the MMKP instances, for which feasible solutions rarely exist. To find good feasible solutions, we introduce a novel repair heuristic based on the tendency function and a genetic search for the function approximation. Even when the density of feasible solutions over the entire solution space is very low, the proposed repair heuristic could successfully change infeasible solutions into feasible ones. Based on the proposed repair heuristic and effective local search, we designed a memetic algorithm that performs well on problem instances with a low density of feasible solutions. By performing experiments, we could show the superiority of our method compared with previous genetic algorithms