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Most of the papers on multi agent RL (MARL) that I have encountered have multiple agents who have a common action space. In my work, my scenario involves *m* numbers of a particular agent (say type A) and *n* numbers of another type of agent. Here the type A agents deal with a similar problem due to which they have the same action space, and type B deal with another type of problem and they have the same action space.

The type A agents are involved in an intermediary task that doesn't reflect in the final reward, and the final reward comes from the actions of type B agents. But the actions of type B are dependent on type A agents. Any idea on what kind of MARL algorithm is suitable for such a scenario?

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In secure flows, the Return to Agent action is a terminating action that ends the flow. This action should only be used in secure call flows initiated by an agent, not in a Transfer to Secure Flow action. Depending on the flow design, adding this action at the end of the secure flow can:

So I've been playing a couple of games on hard and I've noticed that there's something off about the agent success percentages. I had a look around google but most of what I found were discussions about save scumming.

I'm not talking about reloading though. I mean agents trying to assassinate characters over and over with a success rate of 50% or more and failing 5-10 times in a row. At first I put it down to perception bias or something but the chances of a ~50% chance failing repeatedly on multiple occasions are just too low for that.

First time posting here. Recently started working with the Virtual Agent and I'm trying to add an action (Flow) that I have in Power Automate. I believe I have done everything correctly - but clearly I'm missing something as the Flow is no provided for selection.

I created a Flow in My Flows, I subsequently created a new Solution (within the same Environment as the Bot) and added the existing Flow from My Flows. Following these guidelines as suggested: -us/power-virtual-agents/advanced-flow#move-a-flow-to-the-solutions-tab...

However, I still cannot see the Flow when trying to add an action within the authoring canvas. I then found another article suggesting that the Flow should be in the CDS Solution but that doesn't work either. Does anyone have any suggestions to help resolve?

There is a new feature inside call an action to Create a Flow which will spin up a template with a sample input and output string. From there you should be able to easily modify it and insert your custom flow steps in the space just after the initialize variables steps provided.

In Agent Action, you are a skilled agent on a thrilling mission to save the world from destructive Robots. This dynamic online arcade game offers various levels filled with exhilarating shooting adventures. The game is known for its pace, keeping you on the edge as you navigate through different levels seeking out Robots to take down.

This study investigated processes responsible for generative language acquisition through the use of a miniature linguistic system. The miniature linguistic system consisted of nonsense syllables and concrete-enactive, agent-action referents. The purpose of Experiment 1 was to determine (a) whether children would recombine agent and action constituents to produce novel utterances and (b) whether children would generate further extensions of the linguistic system (e.g., agent-action-object sentences) following training of a novel syntactic construction. Four children (aged 8:8, 7:4, 4:9, and 4:5) produced novel utterances to describe untrained agent-action referents. They also progressed from agent-action learning to producing agent-action-object sentences after training on only one or two examples of this sentence type with the appropriate referents. Experiment 2 explored conditions more likely to facilitate recombinative generalization among preschoolers. In particular, how a history of lexical learning affects subsequent language learning was investigated with seven 4-year-olds. Results indicated that a history of lexical learning greatly enhanced generative production of untrained agent-action utterances. In addition, all seven children learned new syntactic rules to generate three-word utterances, regardless of the orderings of agent, action, and object words. Implications for developing efficient language remediation programs are discussed.

The CALL SERVICE agent action is a utility agent action available for many different automation agent types in OTM. This allows an external web service to be invoked from an automation agent. When configuring the CALL SERVICE agent action, the following fields must be specified.

I'm very new to VA and conversation flows so this probably sounds like a dumb question but I can't find out why my script action keeps throwing an error.

My original task was to call a custom script include that checks to see if a functionality pilot exists and then if the user is part of the pilot and returns either yes or no. The script include works perfectly well all over the other parts of the system so the code in it is fine. It is also available to all scopes but written in the global scope. (VA is in a scoped app).

Hi Allen,

My original ask is to get the script include to fire but is was throwing the same error as above. so in debugging, to see why the script action was generating the error, i just went as basic as i could with a log statement.

i have tried gs.info, gs.print, gs.log and gs.debug but the sequence never gets there. it takes a look at the block and just says no thanks. here's your meaningless error. off you go. bye bye.

Oracle Transportation Management supports two types of actions: business object actions and utility actions. Business object actions are specific to the agent type. For example, the action Approve Bill is only available when the Agent Type is BILL. Also, the action Secure Resources is available for an agent type SHIPMENT, but does not make sense for an Agent Type of INVOICE. Utility agent actions are available for all agent types. These include, for example, conditional agent actions (IF, ELSEIF), notifications, and send integration. A list of business object agent actions exists.

An agent has the ability to control the flow of actions using nested IF statements. Oracle Transportation Management includes actions that allow you to add control flow elements to the agent body. Actions within an IF statement are indented to visually indicate the parent-child relationship. There is no limit to the number of levels in which IF statements can be nested.

An agent action defines a set of connected activities. The action is not complete until all activities connected with the action are complete. For example, (depending on the shipment mode and workflow configuration), the Build Shipment action may include moving it to execution and securing resources and therefore this action is not complete until all these related activities finish.

An agent is not transactional. If an error occurs while running an action, changes made to data and state by previous actions are not rolled back. For this reason, an agent may have an Error Handler with a set of actions that run only when the agent detects an error in an action. You can use the Error Handler to set error states, notify interested parties or undo data changes if appropriate. Errors occurring in Error Handler actions are logged and ignored.

Clicking the Show/Hide Statistics button will display/hide agent statistics, such as the Run Time, if they are available. If the Agent statistics level is ACTIONS, each action will show the average and maximum completion time for that action. This time is measured from the time the action begins execution to the completion of the action process. See Configuring Agent Logging and Statistics for more information on using this.

I would then like to have a alert action automatically restart the agent, these devices are only monitored via the agent and do not have an account to connect in via WMI so not sure if that complicates anything.

Pass the Hash. Understand that the SCOM agent will log on with the action account on each and every server, thus loading its credentials in the LSA. What this means is that if any server is compromised, the attacker essentially has a hashed password of an account that is a local admin on all of your servers. If Wdigest is enabled (Server 2008 R2 and below default behavior) they have that same password in clear text.

The default agent action account is the account is used to run workflows on the agent. In an ideal world, this should be set to the local system account. If this is a server admin, this is where pass the hash vulnerability exists.

The minimum described above are the lowest privileges that Operations Manager supports for the action account. Other Run As accounts can have lower privileges. The actual privileges required for the Run As accounts depend on which management packs are running on the computer and how they are configured. For more information about which specific credentials are required, see the appropriate management pack guide.

You must stop and then start System Center Management service if the action account has been configured to use a low-privilege account and this account was added to the required groups while the System Center Management service was running.

The oms client cannot reach the gateway server, because in the properties of the client, the option "Use the following domain or local account to perform agent actions" is checked.

If I change this to "Use the local System", and the service is restarted, the bottom option is checked again.

So I can't save the settings for local system.

Agents make observations using ISensor implementations. The ML-AgentsAPI provides implementations for visual observations (CameraSensor)raycast observations (RayPerceptionSensor), and arbitrarydata observations (VectorSensor). You can add theCameraSensorComponent and RayPerceptionSensorComponent2D orRayPerceptionSensorComponent3D components to an agent's GameObject to usethose sensor types. You can implement the CollectObservations(VectorSensor)function in your Agent subclass to use a vector observation. The Agent class calls thisfunction before it uses the observation vector to make a decision. (If you only usevisual or raycast observations, you do not need to implementCollectObservations(VectorSensor).) 006ab0faaa