Zi Ye

Research has shown that negotiators sometimes misrepresent their emotions, and communicate a different emotion to opponents than they actually experience. Less is known about how people evaluate such negotiation tactics. Building on person perception literature, we investigated in three preregistered studies (N = 853) how participants evaluate negotiators who deceptively (vs. genuinely) communicate anger or happiness, on the dimensions of morality, sociability, and competence. Study 1 employed a buyer/seller setting, Studies 2 and 3 employed an Ultimatum Bargaining Game (UBG). In all studies, participants learned a negotiator’s (the target’s) experienced and communicated emotions (anger or happiness), before evaluating the target. Across studies, targets were evaluated lower on morality if they deceptively (vs. genuinely) communicated anger or happiness. Notably, negotiators deceptively communicating anger were evaluated lower on morality and sociability but higher on competence than those deceptively communicating happiness. Studies 2 and 3 investigated behavioral consequences by examining whether in a future negotiation participants chose the target to be their opponent or representative. Results showed that for opponents, participants preferred targets who genuinely communicated happiness (vs. anger), which was associated with their perceived morality or sociability. For representatives, participants not only preferred targets who had genuinely communicated happiness (vs. anger), but also targets who had deceptively communicated anger (vs. happiness), which was associated with their perceived competence. These findings show that when evaluating deceptive (vs. genuine) communication strategies, people distinguish between morality, sociability, and competence. The importance they attach to these dimensions is also contingent on the behavioral decisions they face.

This paper addresses the adaptive asymptotic tracking control problem for nonlinear systems whose virtual control gains are unknown nonlinear functions of system states. Only in the first step, the Nussbaum gain technique is utilized to handle the uncertain virtual control gain. In the remaining steps, virtual control gains are dealt with by constructing novel control laws without the approximation of the uncertain nonlinear functions and external disturbances by neural networks or fuzzy logic. New adaptive laws are defined to compensate for unknown virtual control gains, uncertain parameters, and external disturbances. Finally, an adaptive tracking controller is designed and applied to the control of a 3-order robot system, which guarantees the boundedness of all the signals in the closed-loop system and asymptotic stability of the tracking error.