Sentence examples for drive the agents from inspiring English sources

The distributed optimization objective is not only to drive the agents to reach a consensus but also to cooperatively minimize the sum of the objective functions of each agent in finite time.

The agent has intrinsic motivations implemented as inborn proclivities that drive the agent in a proactive way.

The behavior of an artificial agent performing in a natural environment is influenced by many different pressures and needs coming from both external world and internal factors, which sometimes drive the agent to reach conflicting goals.

This is one of the few times in "The Inside" when you can actually see the lust for the chase, the will to win, that is at least part of what drives the agents.

This means reprogramming the goal-seeking software that drives the agent.

Examples that utilize a leader include [11] where an auctioneer agent manages bids in the day-ahead market, and [12] where a leader agent is utilized to drive the follower agents' solutions toward a global optimum.

Furthermore, using sliding mode control approach, we design decentralized control inputs for individual agents that use only data from the neighboring agents which directly communicate their state information to the current agent in order to drive the current agent to the desired steady state.

The originality in using belief learning for agent logic is that the agents learn by observing opposing agents' actions without regard for the payoffs that drove the other agents' choices.

The novelty of using belief learning is that agents observe opposing agents' actions without regard for the payoffs that drove the opposing agents to make those choices, form beliefs using these observations, and then make future choices using these beliefs.

Either strong risk aversion or high effort valuation can drive the firm and the agents to favor centralized pricing over delegated pricing.

The use of belief learning to model the dynamics of RAT's offender, target, and guardian behaviors within an agent-based model is original in that the agents learn and adapt given observation of other agents' actions without knowledge of the payoffs that drove the other agents' choices.