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Data Theft Repackaged: A Case Study in Malicious Wrapper Packages on npm
The Socket Research Team breaks down a malicious wrapper package that uses obfuscation to harvest credentials and exfiltrate sensitive data.
Redefining Accounting! Developed by Bfsu Ai-Accounting Team (c) 2023 Github
For detailed installation instructions, see the documentation.
pip install cpagym
import gymnasium as gym
import cpagym as cg
import torch
Num | Action | Unit |
---|---|---|
0 | Discharge of duty | 0 |
1 | Due diligence | 1 |
The observation is a ndarray
with shape (6,)
that provides information about the
two rotational joint angles as well as their angular velocities:
Num | Observation | Min | Max |
---|---|---|---|
0 | Project success rate | 0 | 1 |
1 | Project success return | 0 | 1 |
env = gym.make("Moral_Hazard-v1")#Instantiate the Environment载入道德风险环境
state, info = env.reset(seed=2)#初始化
n_steps = 10
for _ in range(n_steps):
action = env.action_space.sample()#随机行动
state, reward, terminated, truncated, info = env.step(action)
print(observation, reward, terminated, truncated, info )
if terminated or truncated:
observation, info = env.reset()
agent=cg.Agent(state_size=1,action_size=2)#Instantiate the Agent载入会计智能体
env = gym.make("Moral_Hazard-v1")
state, info = env.reset(seed=2)
action = agent.act(state, eps)#最优化行动
next_state, reward, done, _,_ = env.step(action)
agent.step(state, action, reward, next_state, done)
print(agent.memory.memory)
Check out: https://cpanlp.com/reinforcement
FAQs
Accounting Reinforcement Learning GYM for Ai-Accountants .为会计人打造的专属智能会计强化学习框架。
We found that cpagym demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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