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Human team members show a remarkable ability to infer the state of their partners and anticipate their needs and actions. Prior research demonstrates that an artificial system can make some predictions accurately concerning artificial agents. This study investigated whether an artificial system could generate a robust Theory of Mind of human teammates. An urban search and rescue (USAR) task environment was developed to elicit human teamwork and evaluate inference and prediction about team members by software agents and humans. The task varied team members’ roles and skills, types of task synchronization and interdependence, task risk and reward, completeness of mission planning, and information asymmetry. The task was implemented in MinecraftTM and applied in a study of 64 teams, each with three remotely distributed members. An evaluation of six Artificial Social Intelligences (ASI) and several human observers addressed the accuracy with which each predicted team performance, inferred experimentally manipulated knowledge of team members, and predicted member actions. All agents performed above chance; humans slightly outperformed ASI agents on some tasks and significantly outperformed ASI agents on others; no one ASI agent reliably outperformed the others; and the accuracy of ASI agents and human observers improved rapidly though modestly during the brief trials.
composition for wind band lasting approximately 11 minutes. The instrumentation
for the work is as follows: piccolo, 2 flutes, 2 oboes, English horn, 3 clarinets, bass
clarinet, contrabass clarinet, 2 bassoons, contrabassoon, soprano saxophone, alto
saxophone, tenor saxophone, baritone saxophone, 4 horns, 4 trumpets, 2 trombones,
bass trombone, euphonium, tuba, string bass, timpani, 5 percussionists, and piano.
Symphonic Movement: On Works of H. P. Lovecraft is inspired by the horror
fiction writer H. P. Lovecraft. Lovecraft was famous for his ability to create a sense
of creeping dread and terror in his stories. The composition evokes this dark
atmosphere and uses a combination of melodic, harmonic, and orchestrational
devices to imitate this ambience.
The primary musical material of the work is a melody consisting of all twelve
tones. The composition explores this melody through motivic development and
phrase segmentation derived from the source material. This heavy use of
chromaticism helps to create a dissonant and brooding atmosphere throughout. The
work fluctuates between soft, lyrical passages and loud, cacophonous sections. The
alternation of exposed melodic lines with large bombastic climaxes is a major
component of the overall structure of the composition.
The Cripples (Movement I) explores layered rhythms and disjunct melodic fragments which play on the idea of Bruegel’s painting of crippled men trampling over each other and stumbling. Small moments of balance are found throughout only to be lost. Patience (Movement II) is based on an early engraving of Bruegel, which depicts a lone woman who represents a virtue, in this case patience, surrounded by sin and vices. Juxtaposed textures are presented with patience eventually finding itself victorious to temptation. Children’s Games (Movement III) explores a painting which depicts a large number of children playing a plethora of different games. The movement uses graphic notation and plays with the idea of games to create a compositional “game” for the ensemble. Big Fish Eat Little Fish (Movement IV) depicts a large fish eating several smaller fish. A process is introduced which plays on the idea of increasing density and lasts for the bulk of the movement.
A Monte Carlo simulation was used to generate data based on the contextual multilevel model, where sample size, effect size, and intraclass correlation (ICC) of the predictor variable were varied. The effects of simulation factors on parameter bias, parameter variability, and standard error accuracy were assessed. Parameter estimates were in general unbiased. Power to detect the slope variance and contextual effect was over 80% for most conditions, except some of the smaller sample size conditions. Type I error rates for the contextual effect were also high for some of the smaller sample size conditions. Conclusions and future directions are discussed.