Why is Multi-agent Deep Deterministic Policy Gradient (MADDPG) running slowly and taking only 22% from the GPU?

I already asked this question on StackOverflow Where I need to run the Distributed Multi-Agent Cooperation Algorithm based on MADDPG with prioritized batch data code with increasing the number of agents to be 12 agents but it takes a lot of times to train 3500 episodes. I have tried different setting but nothing is working.…

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Unresolved prefixed name: wdt:P195

I have the following string template in java: public static final String SPARQL_QUERY_TEMPLATE_FILTER_MUSEUM_EXPONATES = “PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>” + “select ?thing” + “where” + “{” + ” ?thing rdfs:label \”%s\”@en .” + ” filter exists { ?thing wdt:P195 [] } .” + “}”; String sparqlQuery = String.format(SPARQL_QUERY_TEMPLATE_FILTER_MUSEUM_EXPONATES, exponateName); which when evaluated throws the following error: Exception…

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