Autonomous rendezvous and proximity operation (ARPO) is the basis for various on-orbit services. However, aiming to high-value targets and space debris located on elliptical orbits, ARPO becomes ...challenging for conventional guidance and control methods, due to the complexity and strong nonlinearity of dynamics. This paper proposes a encoder-decoder network with a interconnecting branch between layers to enhance the ability of neural network to operate ARPO on elliptical orbits. Neural network is trained through behavioral cloning, with expert trajectories collected from the optimization results of model predictive control. The performance of the proposed network architecture is effectively improved compared with the existing network architectures, while the computational overhead is greatly reduced compared with model predictive control. We further proposes an event-triggered neural network controller. It uses neural network to calculate control inputs under normal circumstances to save computing resources, and switches to model predictive control to ensure safety and improve control accuracy when events are triggered. To prevent the control input provided by the neural network from exceeding predefined boundaries, constraint violation corrections are added to ensure the safety of the transfer process. Adaptive performance enhancement is implemented to optimize the steady-state relative distance. This mechanism adaptively determines the control thresholds for model predictive controllers and neural network controllers. The proposed approach selects the appropriate controller according to the designed event-triggered conditions, thereby achieving a balance between efficiency and accuracy. Simulation with environment perturbations and sensor measurement noise demonstrates the effectiveness and robustness of the proposed controller.
We propose a new version of the "theory theory" grounded in the computational framework of probabilistic causal models and Bayesian learning. Probabilistic models allow a constructivist but rigorous ...and detailed approach to cognitive development. They also explain the learning of both more specific causal hypotheses and more abstract framework theories. We outline the new theoretical ideas, explain the computational framework in an intuitive and nontechnical way, and review an extensive but relatively recent body of empirical results that supports these ideas. These include new studies of the mechanisms of learning. Children infer causal structure from statistical information, through their own actions on the world and through observations of the actions of others. Studies demonstrate these learning mechanisms in children from 16 months to 4 years old and include research on causal statistical learning, informal experimentation through play, and imitation and informal pedagogy. They also include studies of the variability and progressive character of intuitive theory change, particularly theory of mind. These studies investigate both the physical and the psychological and social domains. We conclude with suggestions for further collaborative projects between developmental and computational cognitive scientists. (Contains 5 figures.)
In his review, Ramsey (2018) argues that it is currently unclear what reaction time indices of automatic imitation measure due to lacking research on their validity and domain-specificity. In our ...commentary, we argue that this conclusion is based on two misconceptions, namely that automatic imitation was designed as a laboratory measure of motor mimicry and that psychometric approaches to validity can readily be applied to experimental settings. We then show that reaction time indices of automatic imitation measure covert imitative response tendencies. Furthermore, while irrelevant for their validity, we argue that these indices are associated with some, but not necessarily all, types of overt imitation. Finally, we argue that mapping out the brain networks does not suffice to understand the brain processes underlying imitative control.
Technology licensing involves the simultaneous competition and collaboration between the partnering organizations (“coopetition”). This paper investigates resource-based, market-based, and ...imitation-based motives in technology licensing partner selection. Using the theoretical foundations of these diverse motives, we identify drivers related to whether firms license-in technologies from science-based organizations (i.e., universities, government, and research institutes) and competitors. Using 307 patent licenses, we found that technological similarity has differing impacts on the choice of science-based organizations and competitors. Our results show that there is an inverted U-shaped relationship between technological similarity and choice of competitors, while a U-shaped relationship exists between technological similarity and choice of science-based organizations. We also find that when there are a large number of product-market entries, firms tend to license technologies from competitors. These results confirm that the drivers of technology licensing partner selection vary depending on firms' diverse motivations.
•Technology licensing partner selection is driven by diverse coopetition motives.•U-shaped relationship; technological similarity and selecting science-based partner.•Inverted U-shaped relationship; technological similarity and selecting competitor.•Product market entries positively impact choice of competitors in license alliances.
•This article formulates the Air Traffic Controllers’ (ATCOs’) reaction problem;•proposes a data-driven method simulating the uncertainty in the trajectories’ evolution;•proposes a methodology for ...evaluating methods resolving the ATCOs’ reaction problem;•proposes using a Variational Auto-Encoder to model ATCOs’ reactions;•evaluates the proposed method using real world data, also w.r.t. a baseline method.
With the aim to enhance automation in conflict detection and resolution (CD&R) tasks in the Air Traffic Management domain, this article proposes deep learning (DL) techniques that model Air Traffic Controllers’ reactions in resolving conflicts violating aircraft trajectories separation minimum constraints: This implies learning when the Air Traffic Controller reacts towards resolving a conflict, and how he/she reacts. Timely reactions, to which this article aims, focus on when do reactions happen, aiming to predict the trajectory points, as the aircraft state evolves, that the Air Traffic Controller (ATCO) issues a conflict resolution action. Towards this goal, the article formulates the Air Traffic Controllers’ reaction prediction problem for CD&R, presents DL methods that can model Air Traffic Controllers’ timely reactions, and evaluates these methods in real-world data sets, showing their efficacy in solving the problem with very high accuracy.
This study draws on resource orchestration theory to develop and test a framework that explains when the imitation of business models from other industries increases new venture growth. We propose ...that extra-industry business model imitation enhances growth when extra-industry business models are bundled together with novel technologies, and when founders possess the necessary industry experience to orchestrate these resource combinations effectively. Using a unique multi-source, time-lagged dataset of 122 Swiss technology ventures from four industries, we find support for our theoretical model and discuss its implications for research at the intersection of business models, competitive imitation, and resource orchestration.
The Social Side of Imitation Over, Harriet; Carpenter, Malinda
Child development perspectives,
March 2013, Volume:
7, Issue:
1
Journal Article
Peer reviewed
Children's imitation is a profoundly social process. Although previous developmental accounts of imitation have focused on imitation as a way to learn from others, the current article stresses that ...imitation goes far beyond this: It is often intimately tied to children's need to belong to the group and their drive to affiliate with those around them. Accordingly, imitation is chiefly determined by the social motivations and pressures children experience within both interpersonal and intergroup settings. This perspective resolves an apparent paradox in the empirical literature, explaining why children sometimes copy selectively and sometimes copy faithfully (so‐called overimitation). It also situates the developmental and comparative study of imitation and cultural transmission within a broader social‐psychological framework, uniting it conceptually with research on mimicry, conformity, normativity, and group membership.
This study investigates interpersonal processes underlying dialog by comparing two approaches, interactive alignment and interpersonal synergy, and assesses how they predict collective performance in ...a joint task. While the interactive alignment approach highlights imitative patterns between interlocutors, the synergy approach points to structural organization at the level of the interaction—such as complementary patterns straddling speech turns and interlocutors. We develop a general, quantitative method to assess lexical, prosodic, and speech/pause patterns related to the two approaches and their impact on collective performance in a corpus of task‐oriented conversations. The results show statistical presence of patterns relevant for both approaches. However, synergetic aspects of dialog provide the best statistical predictors of collective performance and adding aspects of the alignment approach does not improve the model. This suggests that structural organization at the level of the interaction plays a crucial role in task‐oriented conversations, possibly constraining and integrating processes related to alignment.
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