We investigate decentralized quadratic cheap talk and signaling game problems when the decision makers (an encoder and a decoder) have misaligned objective functions. We first extend the classical results of Crawford and Sobel on cheap talk to multi-dimensional sources and noisy channel setups, as well as to dynamic (multi-stage) settings. Under each setup, we investigate the equilibria of both Nash (simultaneous-move) and Stackelberg (leader-follower) games. We show that for scalar cheap talk, the quantized nature of Nash equilibrium policies holds for arbitrary sources; whereas Nash equilibria may be of non-quantized nature, and even linear for multi-dimensional setups. All Stackelberg equilibria policies are fully informative, unlike the Nash setup. For noisy signaling games, a Gauss-Markov source is to be transmitted over a memoryless additive Gaussian channel. Here, conditions for the existence of a ne equilibria, as well as informative equilibria are presented, and a dynamic programming formulation is obtained for linear equilibria. For all setups, conditions under which equilibria are noninformative are derived through information theoretic bounds. We then provide a different construction for signaling games in view of the presence of inconsistent priors among multiple decision makers, where we focus on binary signaling problems. Here, equilibria are analyzed, a characterization on when informative equilibria exist, and robustness and continuity properties to misalignment are presented under Nash and Stackelberg criteria. Lastly, we provide an analysis on the number of bins at equilibria for the quadratic cheap talk problem under the Gaussian and exponential source assumptions. Our findings reveal drastic differences in signaling behavior under team and game setups and yield a comprehensive analysis on the value of information; i.e., for the decision makers, whether there is an incentive for information hiding, or not, which have practical consequences in networked control applications. Furthermore, we provide conditions on when a ne policies may be optimal in decentralized multi-criteria control problems and for the presence of active information transmission even in strategic environments. The results also highlight that even when the decision makers have the same objective, presence of inconsistent priors among the decision makers may lead to a lack of robustness in equilibrium behavior.