The phrase "agent policy" is correct and usable in written English.
It can be used in contexts related to rules, guidelines, or procedures that govern the actions of an agent, often in fields like business, insurance, or technology.
Example: "The agent policy outlines the responsibilities and expectations for all representatives in our organization."
Alternatives: "representative guidelines" or "agent protocol".
Change agent, policy expert, movement builder, and community leader are all ways to describe Vien Truong, CEO of Dream Corps.
While Treasurer Cowell publicly acknowledged the importance of adopting a pay-for-play and placement agent policy in 2009, disclosure has not meaningfully improved during her tenure.
Assuming that the Treasurer has enforced compliance with the placement agent policy (which requires disclosure of the fees paid to her), the relevant information is readily-available — indeed already known to her.
What reinforcement learning concerns, given a set of actions taken from some states and the rewards thus received, is how to improve the Agent policy in such a way as to increase the expected return ({mathbb {E}}[G]).
The goal now is to update the agent policy (pi) from the prior policy (pi _{Prior}) in such a way as to increase the expected score for the generated sequences.
The union filed a new antitrust lawsuit on December 30 asking federal judge David Doty to overturn the league's restricting free agent policies.
Moving the relevant information from research centers to extension agents, policy makers and farmers has been a more frequent limitation.
In marketing, states regulate advertising, licensing of agents, policy forms and wording, service and process procedures for handling claim disputes, expense allowances for acquiring new business, and other agency and insurer operations, including being admitted to do business in the state.
The NFLPA went on strike for a month in 1987 upon the expiration of the 1982 CBA; the league's free-agent policy was the major matter in dispute.
Policy: An agent's policy determines what action will be selected in a particular state.
That said, in many settings training multi-agent policies using single-agent RL algorithms can yield surprisingly strong results.
